chapter 4 hardware implementation of hardware...

=== Industrial Fault Detection And Fuzzy Diagnosis System for Textile Industry ===

Chapter 4 Hardware Implementation of Fault Detection and Fuzzy Diagnosis 127

Chapter 4

Hardware Implementation of Fault Detection and

4.1 Introduction

The Textile Industry has reached at a highly resourceful stage in

manufacturing of different types and qualities of fabrics. The fabric formation

process of late is fully automated with the help of Electronic Technology and

can be controlled to the lowest level down to each cross of warp and weft.

Today Textile Industry is having Electronic Systems to ease the operation of

different types of machines and plays an imperative role in the automation.

Multiple sections and departments of fabric development process are

interconnected to form a network which will lead to the centralized monitoring

and can control the process from remote location. Continuous operation of the

machines is therefore accomplished and eventual machine breakdowns can be

reported instantly to the central station. Embedded Systems played a vital role

in the formation of the network of these systems. The individual node in the

embedded network can collect the information of various faults detected from

the machine in Textile Mill. The fault information accumulated by the different

nodes will then be sent to the centralized location in message format. However

the noise factor in the Textile Mill is high enough to alter the fault signals

throughout the communication between the faulty machine and the Centralized

Fault Detection System. In the developed system the Controller Area Network

(CAN) protocol has been implemented for the communication purpose. The

CAN protocol is highly immune to noise and designed purely for the industrial

environment where noise susceptibility over communication medium is higher.

The message information gathered will then be passed over to the

Personal Computer called ‘host’ where the information must need to be

analyzed to determine-

The exact fault condition,

Behavior of the fault,

Chapter 4

Hardware Implementation of

Fault Detection and Fuzzy Diagnosis



Reason of the fault,

Damages to the machine due to fault and

Possible remedial action for the particular fault condition.

Generally the fault occurrence behavior is uncertain and unpredictable in

nature, and it can be arise due to single or multiple conditions those can be non-

repeatable and therefore the remedies for such faults can be different depending

upon the fault occurrence behavior. The number of different solutions or

remedies can be therefore being worked out on trial-and-success base by the

fault handling Engineers. This makes difficult to generalize the fault condition

and may lead a Fault Diagnosis System be ill-defined and complicates the task

for conventional fault diagnosis and fault processing algorithms. This tenders a

space to exploit the fault diagnosis system using underlying principles of Fuzzy

Logic. The Fuzzy Expert System (FES) and Fuzzy Logic Control (FLC) are

the two avenues where fuzzy logic has been practically exploited to a great

extent [1]. This is mainly due to success of traditional Expert Systems and

conventional controls in past. FES is based on the semantic manipulation and

approximate reasoning in the process of inferring conclusions. It can prioritize

the conclusions provided by the different Experts to solve the fault condition.

FES has ability to handle the situations where similar fault can occur with

different condition by rule base approach where rules pervaded with ambiguity.

It processes the imprecise information and has ability to reason. In other words

FES is computer-based system that emulates the reasoning process of a human

Expert within a specific domain of knowledge using the apparatus of

Approximate (Fuzzy) Reasoning.

The architecture of the system having different kinds of machines of

multiple sections/departments of the Textile Industry interconnected to each

other within the network is shown in Fig. 4.1.There are different sections in the

Textile Industry. However Spinning Department and Weaving Department

have been chosen for the implementation of Fuzzy based Fault Diagnosis

System. These departments are equipped with very high speed, fully automated



systems to gain the maximum throughput with respect to time and are made to

run for twenty four hours to produce finest quality products. The process stages

Node S1

Machine 1

Node S3

Machine 3

Node S2

Machine 2

Node S4

Machine 4

Spinning Department

CAN

Bus

CAN

Bus

Node W1

Machine 1

Node W3

Machine 3

Node W2

Machine 2

Node W4

Machine 4

Weaving Department CAN

Bus

CAN

Control Room

Fuzzification Module

Rule Base & Database

Defuzzification Module

Inference Engine

Personal Computer

HOST Controller

Fig. 4.1: Overview of Fault Diagnosis System for Textile Industry



in these two departments are dependent on each other and need to work in

perfect synchronism for maximizing the produce. The breakdown in one

process stage can therefore halts the total production line following it and an

immediate solution is required to regain the synchronism, otherwise can results

in to calamitous financial losses. The system is therefore required to attend

with priority and an immediate remedy to be initiated circumventing the

breakdown condition or it requires call for an Expert Engineer to seek the

solution. The intelligent system instigating the alert before happening of

undesirable breakdown and capable of taking initiating multiple remedies to

choose from the Superior rather than waiting for an arrival of an Expert could

be highly appreciable.

The system shown in the architecture (Fig.4.1) is intends to monitor

multiple machines and their behavior according to the change in the input

electrical and/or mechanical parameters and capture any anonymous behavior

which can cause a fault. The change in behavior of the machine is then

identified for possible condition of fault. Different kinds of faults generated by

the different machines are acquired by an appropriate signal conditioning units.

The fault information accumulated by the local controller is then send to the

central controller by the means of high speed CAN network. The central node

then prioritizes the fault information and send them to the processing unit i.e.

PC where a Fuzzy Inference System designed in MATLAB analyses the faults

according to the machines and evaluates the fault condition to provide an

timely and veracious solution to recover the system from faulty condition.

As there are multiple causes of faults, there exist multiple remedies to

resolve them. These remedies can be derived straight forward from manual, or

from the experienced Operators or from the different Experts working with

same systems or can be from the Researchers doing progressive investigations

to find the better and better solution. The system presented here is able to

provide the optimal among these multiple remedies prioritized by the ease of

implication of the solution to save the time and cost.



4.2 Fault Collection Unit

The basic fault collection unit aims the gathering of electrical states as

information which is then identified as fault if any outbound condition may

happen to halt the machine functioning. The identified faults are categorized

according to their electrical behavior as Digital faults and Analog faults. The

outbound condition can be different for different machine according to its role

in the process, but the electrical means of change can be distinguished by the

state of its electrical data. Change in voltage, current and physical parameters

etc. can be identified by the means of analog sections whereas logical change is

classified in digital information which can be sensor failure, emergency stop,

automatic machine breaking etc.

The Fault collection unit performs the role of watchman of the system

which collects the status of the information, converts it to the meaningful form

and sends to the central system periodically. It is mainly responsible to

congregate correct status information of the particular machines by means of

analog and/or digital signal conditioning system to get transformed in to the

meaningful form. The general block diagram of fault collection unit containing

various sensors and associated signal conditioning unit is shown in Fig. 4.2. To

suite the parameter state for the acquisition, the analog sensors providing

analog output employed in the system are connected to the analog signal

conditioning section that can be an amplifier or attenuator. The analog output is

then provided to the different channels of the ADC built-in in the

microcontroller which encodes the analog data to the digital form. The digital

states of the machines are acquired through the digital conditioning section

which can be level shifter and/or inverter according to the electrical parameter

state.

The collected information is stored in the microcontroller temporarily

and sent to the central unit through the high speed CAN bus. A CAN

transceiver is attached to microcontroller to form a communication link

between the Fault collection unit and Central unit from which data information



can be exchanged. The provision for optional local display is made to ease

viewing/ debugging the machine states to the Operator/Engineer.

4.3 Environment Fault Collection

Many properties like weight, tensile strength, elastic recovery etc. of

textile materials vary considerably with moisture regain, which in turn affected

by the ambient Relative Humidity (RH) and Temperature. Therefore the

measurement and recording of Temperature and Humidity at test locations

either continuously or at regular intervals is anticipated. The block diagram of

Environment fault collection unit is shown in Fig. 4.3. Both Temperature and

Humidity sensor in the block diagram gives the analog output going through

signal conditioning built using high gain operational amplifier. The inbuilt

ADC in the intelligent microcontroller converts the sensor’s output in digital

form for further processing. Temperature and Humidity data is then calibrated

CAN Bus

Analog Sensor

Microcontroller

Signal

Conditioning

Optional Local Display

CAN Transceiver

Analog Sensor

Digital Fault

Signal

Conditioning Digital Fault

Fig. 4.2: General Block Diagram of Fault collection unit



and displayed on local display and finally transferred to the Central Unit

through CAN communication bus for fault analysis purpose.

4.3.1 Temperature Measurement

The atmospheric conditions with respect to temperature and humidity

play very domineering part in the manufacturing process of textile yarns and

fabrics. Mechanical properties of fibers and yarns also depend on the

surrounding temperature conditions to which these are exposed during the

textile process. Due to high heat dissipation from spinning as well as weaving

and knitting equipment there is a significant increase in temperature

particularly in the vicinity of the machinery and their driving motors.

The natural wax covering cotton fibers softens at these raised

temperature conditions, thereby adversely affecting the lubricating property of

wax for controlling static and dynamic friction. Increase in temperature beyond

the design limit also reduces the relative humidity condition near the

processing elements of the machinery. Hence textile air-engineering design has

CAN Bus

Fig. 4.3: Block Diagram of Environment Fault

Temperature Sensor

Microcontroller

Signal

Conditioning


CAN Transceiver

Relative Humidity



to take care of controlled air flow within the textile machinery for dissipating

heat generated at the source and it is customary to carry the waste heat along

with the return air to the return air trench. The quantity of return air going to

exhaust or recirculation is regulated for controlling the inside design

conditions. Modern spinning equipment is designed to operate at high spindle

speed. However, high ambient temperature always tends to curtail the operation

speed of the machine. Moreover, the sophisticated electronic controls in

modern textile machinery also require that the inside temperature in the

department should not exceed 33°C or so.

It is also necessary to limit the range of temperature to which the textile

machinery is exposed, since the structure of the machinery containing many

steel and aluminum parts which expand at different rates with temperature rise

(due to difference in co-efficient of thermal expansion) will be subjected to

mechanical stress. Hence, along with maintenance of stable relative humidity

conditions recommended for different textile processes, it is equally desirable

to maintain the temperature level within a range, without much fluctuation.

Recommended temperature values are from 20 to 250C for different

material cotton, wool, linen, ribbons, knitwear, carpets for different

applications like carding, spinning, weaving. For nylon/perlon the

recommended temperature values ranges from 20 to 270C. The Integrated

Circuit Temperature Sensors offer another alternative to solving temperature

measurement problems. The advantages of integrated circuit silicon

temperature sensors includes the user friendly output formats and ease of

installation in the PCB assembly environment. The LM35 is precision

integrated-circuit temperature sensors, whose output voltage is linearly

proportional to the Celsius (Centigrade) temperature [2].

4.3.2 Humidity Measurement

The environmental conditions with respect to temperature and humidity

play very central part in the manufacturing process of Textile Industry. Many



properties of textile materials vary considerably with moisture regain, which in

turn affected by the ambient Relative Humidity (RH). Therefore Humidity

sensors have attracted a lot of attention in Textile industrial field. Different

methods are used for measurements humidity, e.g., changes in mechanical,

optical, and electrical properties of the gas water vapor mixtures [3]. Three

types of humidity sensors feasible for present measurement could be-

1) Resistive humidity sensor,

2) Thermal conductivity humidity sensor,

3) Capacitive humidity sensor.

Resistive humidity sensors measure the change in electrical impedance

of a hygroscopic medium such as a conductive polymer, salt, or treated

substrate. The impedance change is typically an inverse exponential

relationship to humidity. The response time for most resistive sensors ranges

from 10 to 30 seconds for a 63% (RH). The impedance range of typical

resistive elements varies from 1 KOhms to 100MOhms. In residential and

commercial environments, the life expectancy of these sensors is greater than 5

years, but exposure to chemical vapors and other contaminants such as oil mist

may lead to premature failure. Another drawback of some resistive sensors is

their tendency to shift values when exposed to condensation if a water-soluble

coating is used.

Thermal conductivity humidity sensors measure the absolute humidity

by quantifying the difference between the thermal conductivity of dry air and

that of air containing water vapor. An interesting feature of thermal

conductivity sensors is that they respond to any gas that has thermal properties

different from those of dry nitrogen, this will affect the measurements.

Absolute humidity sensors are commonly used in appliances. In general,

absolute humidity sensors provide greater resolution at temperatures >200°F

(93°C) than do capacitive and resistive sensors, and may be used in

applications where the other sensors would not survive.



Capacitive relative humidity sensors are widely used in industrial,

commercial, and weather telemetry applications. They consist of a substrate on

which a thin film of polymer or metal oxide is deposited between two

conductive electrodes. The sensing surface is coated with a porous metal

electrode to protect it from contamination and exposure to condensation. The

substrate is typically glass, ceramic, or silicon. The incremental change in the

dielectric constant of a capacitive humidity sensor is nearly directly

proportional to the relative humidity (RH) of the surrounding environment.

The change in capacitance is typically 0.2-0.5 pF for a 1% RH change, while

the bulk capacitance is between 100 and 500 pF at 50% RH and 25°C.

Capacitive sensors are characterized by low temperature coefficient, ability to

function at high temperatures (up to 200°C), full recovery from condensation,

and reasonable resistance to chemical vapors. The response time ranges from

10 to 60 s for a 63% RH step change [4].

Recommended temperature and humidity values for various textile

applications are from 50 to 90 % RH for Spinning. For weaving section the

humidity requirement is changes accordingly the types of cloths. For example

cotton requires 60 to 70 % RH, wool requires 55 to 65 % RH, and linen

requires 70 to 75 % RH. According to survey the humidity should be between

50 to 80 % RH for weaving purpose. For carding or combing machine the

recommended humidity is somewhat high up to 85%. Textile manufacturing

process involves the following sequence.

Raw cottonFiber makingYarn making (spinning)Fabric making (weaving/knitting)

The sequential steps during the processes of fiber making, yarn making

and fabric making in the production of textiles along with the required relative

humidity conditions to be maintained at each stage of processing in the textile

process are discussed in the following sections. From 'carding' till 'roving', the

loosely bound fibers are vulnerable to static electricity in dry and brittle

condition due to static and dynamic friction. This also creates dust and fiber fly

(fluff). Higher moisture content lowers the insulation resistance and helps to



carry off the electrostatic charge. Hence relative humidity (being related to

moisture content) needs to be maintained above the lower limit of relative

humidity range, specified for various textile processes so as to avoid the

problems of yarn breakage in dry and brittle condition and also minimize the

buildup of static charge so as to reduce dust and fiber fly (fluff).

At the high moisture limit (i.e. above the upper limit of relative humidity

for the process) fibers tend to stick and lead to form the laps on the rolls which

disrupts the production process. Removal of laps involves a manual activity

and hence time consuming process. Weaving rooms for cotton fabric making

are designed to maintain high relative humidity of 80% to 85% at the warp

sheet level i.e. at 'loom sphere' as high humidity helps to increase the abrasion

resistance of the warp. It is required to maintain the general humidity condition

in the room at around 65% RH. Knitting operation also requires a stable

relative humidity condition at 55% ± 5% for precise control of yarn tension.

Hence it is vital to maintain stable relative humidity conditions within the

prescribed tolerance limits at all steps of textile processing.

SY-HS220 [5] is humidity sensor with the analog output and has to be

connected to the A/D convertor pin of the microcontroller with intermediate

stage of Op-Amp buffer to avoid loading on the microcontroller port. It

operates at 5V with the minimal current consumption less than 3.0mA and

sensing range spreads over 30% to 90% of relative humidity with 5% of

accuracy. The humidity sensor module comes with temperature compensation

circuit with internal linearly calibrated output in the form of voltage.

The full circuit diagram of the Environmental Fault Collection Unit is

shown in the Fig. 4.4.



D5

1N4007

U9

MC

P2551

12345 6 7 8

TXDVS

SVD

DR

XDVR

EFC

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CAN

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LED

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7912

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GND

+5V

BU

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C3

0.1uF

+5V

+5V

C19

33pF Temperature

C14

0.1uF

- +U

2A

LM358

321

84

J3C

ON

3

123

+5V

RESET

+C

231000uF 25V

R25

150E

+5V

Hum

idity

SW1

RESET SW

Tempe

rature

Sensor

- +U

4A

LM358

321

84

+5V

Q1BC

557

J4PR

OG

12345

R13

10k

D10

LED

Power

Supply

RX

C16

0.1uF

+5V

R21

330E

C4

0.1uF

U5

7812

13

2

VINV

OU

T

GND

C18

0.1uF

U10

PIC18F2480

9

18 19 20

1234567821 22 23 24 25 26 27 28

101112131415 16 17

OS

C1/C

LK1/RA7

RC

7/RX/D

TVS

SVD

D

MC

LR/VPP/R

E3

RA

0/AN0

RA

1/AN1

RA

2/AN2/VR

EF-R

A3/AN

3/VREF+

RA

4/T0CKI

RA

5/AN4

VSS

RB0/IN

T0/AN10

RB1/IN

T1/AN8

RB2/IN

T2/CAN

TXR

B3/CAN

RX

RB4/KBI0/AN

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B5/KBI1/PGM

RB6/KBI2/PG

CR

B7/KBI3/PGD

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C2/C

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C2/C

CP1

RC

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RC

4/SDI/S

DA

RC

5/SDO

RC

6/TX/CK

Temperature S

ensor

123

R6

20K

C9

0.1uF

LCD

Displa

y

J2

Buzzer/Hutter

12

D4

1N4007

Y1

4MH

z

+5V

C11

0.1uF

Hum

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123

J12

LCD

12345678910111213141516

Hum

idity

C20

33pF

LED

PG

D

U7

7805

13

2

VINVO

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GND

R18

120E

+5V

R24

330E

TX

R11

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C17

0.1uF

+5V

Humid

ity Se

nsor

PG

C

CAN In

terfac

e

C15

0.1uF

+5V

+5V

+5V

LEDR

ESET

C7

0.1uF

+

C24

1000uF 25V

+5V

D7

1N4007

Temperature

Fig. 4.4: Circuit Diagram of Environment Fault Collection Unit



4.4 Motor Fault Signal Collection

AC Induction Motors are used as actuators in many industrial processes

[6]. Although induction motors are reliable, they are subjected to some

undesirable stresses and cause faults resulting into failure. Monitoring of

induction motor is a fast emerging technology for the detection of initial faults.

It avoids unexpected failure of Textile process. Though the probability of

breakdowns of Induction motors is very low, the fault diagnosis has become

almost indispensable for industry. Particularly when they are working in

sophisticated automated production lines. To decrease the machine down time

and improve stability the on-line diagnostic features are to be necessarily

incorporated with the drives. In modern Textile Industry lots of machines

depend on mutual operation and the cost of unexpected breakdowns figures out

to be very high. Thus condition monitoring techniques comprising of fault

diagnosis and prognosis are of great concern in industry and are gaining

increasing attention. From the foregoing analysis it is clear that the appearance

of various faults is simply determined by the stator current values. In general

stator currents and voltages are preferred because the sensors required are

usually present in the drive considered. The block diagram of Motor fault

collection unit is as shown in Fig. 4.5. The Current Transformer (CT) is used as

the current sensor and the Voltage Transformer (VT) is used as the voltage

sensor. The frequency is measured using the Zero Crossing Detector (ZCD)

circuit. With the help of waveforms from ZCD, the microcontroller measures

the time period for one cycle and hence the frequency. The current, voltage

and frequency values are gathered through the microcontroller and the

calibrated data is transferred to the Central unit via the CAN bus.

4.4.1 Current Measurement

The measurement of instantaneous, peak, or average values of the

voltage and current signals are necessary to monitor for protecting or



controlling the electrical systems. Hence, accuracy of current measurement

plays an essential role in the dynamic performance, efficiency, and safety of an

electrical system. Application of current sensing in motor control forms the

significant part of Motor Fault Detection. There are different techniques used

for current sensing as described in following sub-sections.

4.4.1.1 Current Measurement: Series Resistance Method

A low valued resistance placed in the current path of a circuit translates

the current in to a voltage. This voltage signal is a representation of the current,

which can be easily measured and monitored by control circuitry. The sense

resistor- the resistor used for current measurement must have low resistance to

minimize its power consumption [7]. Resistive-based current sensors are

acceptable where the power loss, low bandwidth, noise and non-isolated

measurement are acceptable. These sensors are not used in high power

applications where isolation is required. Solution to these problems could be

electromagnetic-based current sensing techniques.

CAN Bus

Fig. 4.5: Block Diagram of Motor Fault collection unit

Current Sensor

Microcontroller

Precision

Rectifier


CAN Transceiver

Voltage Sensor

Zero Crossing Detectors



4.4.1.2 Current Measurement: Electromagnetic Based Current Sensing

Sensing the magnetic field surrounding a conductor provides

information about its current. Electromagnetic-based techniques based on this

phenomenon provide galvanic isolation between the control and power stages,

higher bandwidth, and lower power losses. The lower power dissipation of

electromagnetic-based current sensors allow much higher signal level,

significantly improves the signal-to-noise environment of the control system

[7]. It is mainly divided into two different segments based on the core material

used to wound the coil. First type is nothing but a Current Transformers that

utilizes ferrite or iron material as core for the coil, whereas second type uses air

as core and known as Rogowski Coil.

4.4.1.3 Current Measurement: Using Current Transformers

A current transformer (CT) is similar to a transformer, except that the

primary input is a current. CT is used with low range ammeters to measure

currents in high voltage circuits. In addition to providing insulation from the

high voltage side, CT steps down the current in a known ratio. Their physical

basis is the mutual induction between two circuits linked by a common

magnetic flux. A CT consists of two inductive coils, which are electrically

separated but magnetically linked through a path of low reluctance, as shown in

Fig.4.6. If one coil is connected to an ac source, an alternating flux is set up in

the core, most of which is linked with the other coil in which it produces

mutually induced electromotive force (EMF) according to Faraday’s law of

electromagnetic induction. The first coil is called the primary coil, and second

coil is called the secondary coil of the CT. If the secondary of the CT is closed,

electric energy is magnetically transferred from primary to secondary.



For an ideal transformer with no load, the induced secondary EMF is

same as the secondary terminal voltage (VS). The relationship between the

primary and secondary voltages, currents, and number of turns is given by

(4.1).

(4.1)

Where VP and VS are primary and secondary terminal voltages, IP and IS

are primary and secondary winding currents, and and are the number of

primary and secondary turns, respectively. The maximum input current of a CT

can be increased by varying the ohms of the burden resistor. Lowering the

ohms of the burden resistor will increase the maximum input of the CT, but it

lowers the resolution. Also, the accuracy of the output voltage depends on the

accuracy of the burden resistor. The burden resistor should never be used for

more than 55 % of its wattage capacity, and thermal concerns of the

surrounding materials should be considered to prevent over heating damage.

For circuits requiring very accurate outputs, the CT should only be used up to

50 % of saturation line of core. In our work we utilized the Ring type CT

having a Ferrite core. The specifications of the CT used are listed in table 4.1.

Source Vs

Is Ip

A Ns Np

Fig. 4.6: Current Transformer [7]



Table 4.1 Electrical Specifications of Current Transformer

1 Type : Ring

2 Sub Type : Tape insulated ring type

3 Primary Current : 30 Amp

4 Secondary Current : 3 Amp

5 Burden : 5VA/ 10VA/ 15 VA.

6 Frequency : 50 Hz

7 Operating Temp. : - 10 deg. C to 65 deg. C.

4.4.1.4 Current Measurement: Using Air Core

The performance of a CT is often limited by the characteristics of its

magnetic core material (hysteresis, non-linearity, losses, saturation, remanence

(residual flux) therefore, the design of an air core or coreless transformer is

often considered. The challenge with air core current measurement techniques

is to achieve measurement sensitivity and to be insensitive to external magnetic

fields. The Rogowski Coil is a simple, inexpensive and accurate approach for

current measurement. Structure of a Rogowski Coil is similar to a CT.

However, instead of an iron core, Rogowski Coil is based on air or ironless

bobbins with hundreds or thousands of turns, as shown in Fig. 4.7. The

Rogowski Coil has an air core, so it will never get saturated and its output of

remains linear for high current measurement [8-10].

Fig.4.7: Rogowski Coil current [10]

Amp.



4.4.2 Line Voltage measurement

Voltage transformers (VT) operate under the principle of

electromagnetic induction between two electric circuits by means of a mutual

magnetic flux. The standards establishing the performances of the voltage

transformer is an instrument transformer in which the secondary voltage is

substantially proportional to the primary voltage and differs in phase from it by

an angle which is approximately zero for appropriate direction of the

connections. The VT usually consists of two electric windings (the primary and

secondary circuits), both wound around a magnetic core as shown in Fig. 4.8.

The number of turns of each winding characterizes both circuits: N1 is the

number of turns of the primary circuit, and N2 is the number of turns of the

secondary circuit. The operation principle of a V.T. [11] is based on the

Faraday Induction Law. In accordance with this law, when the primary winding

is connected in parallel with the alternative high voltage to be measured as

indicated in Fig.4.9, a magnetic flux is created as indicated in the equation (4.2)

(4.2)

This magnetic flux is guided by the magnetic core, which links the primary and

secondary windings, and induces a secondary voltage given by equation (4.3).

(4.3)

Thus, it is possible to measure the primary high voltage u1(t) by means of the

secondary voltage, u2(t), which is proportionally reduced and galvanically

insulated from the high voltage part. The relationship between the primary

voltage and the induced secondary voltage (transformation ratio) is given in

equation (4.4)

(4.4)

The secondary voltage causes a current i2(t) to flow in the secondary circuit

when a load is connected. The current i2(t) is determined by the total

impedance of the secondary circuit (ideally, for the load). The current in the

primary is also depending of the load and can be obtained considering that



power in both sides is kept constant (no losses).

(4.5)

(4.6)

For instance, the main criterion behind choosing the primary and

secondary winding gauges is the limitation on errors (i.e., reduction of voltage

drops) in the case of voltage transformers. The capacity or burden of the VTs is

very low, and size is determined by the system voltage on which the VT is to

be used. The exciting current of a VT will also be much larger relative to the

burden. The accuracy depends on the leakage reactance and the winding

resistances which determine how the errors vary as the burden on the secondary

increases. The permeability and the power dissipation of the core affect the

exciting current and hence the errors at zero burden. Standards for voltage

transformers specify errors that must not be exceeded for various classes of

accuracy. Limitation in errors leads to limits of watt loss and magnetizing

current. The effect of this is to reduce the working flux density of the voltage

transformer as compared to the power transformer. Care must also be taken in

designing the winding, as the winding resistance and reactance affect errors.

I1(t) I2(t) 1=2=c

N2 N1 u1(t) u2(t)

2

Fig. 4.8: Ideal model of VT. Resistance of winding and non-linearity of core have not been considered



4.4.3 Line Frequency Fault Measurement

The frequency of a power system is an important operational parameter

for the safety, stability and efficiency of the power system. Reliable frequency

measurement is prerequisite for effective power control, load restoration and

system protection. Therefore, there is a need for fast and accurate estimation of

the frequency of the power network using voltage waveforms.

Several digital methods for the frequency measuring have been proposed

in the past few decades. The use of the zero crossing detection and calculation

of the number of cycles that occur in a predetermined time interval [12] is a

simple and well-known methodology. Measurement of frequency turns out to

be more complicated and involves two main issues, one is obtaining an isolated

sample of the line voltage and another is measuring the frequency. For safety

reasons, it is essential to isolate the measuring electronics circuit from the

power line. Isolation methods, such as a transformer, or optical couplers are

available among which the Voltage Transformer is used for sampling the line

voltage. The frequency measurement circuit shown in Fig. 4.9 generates an

output square wave to use with TTL logic (0 to +5V range) from an input wave

of any amplitude up to 100 volts. R1 combined with D1 and D2, limits the

swing to 0.6V to +5.6V approximately. Resistive divider R2-R3 is necessary to

limit negative swing to less than 0.3 V, the limit for LM358 comparator. R5

and R6 provide hysteresis, with R4 setting the trigger points symmetrically

about ground. The input impedance is nearly constant, because of the large R1

value relative to the other resistors in the input attenuator [13].

4.5 Oil Tank Fault Collection

Every mechanism needs the lubrication in one or another form. But

outside of the spinning frame no other class of machinery claims so much

attention from the lubricant standpoint as looms. To withstand the continuous

wear and tear process it is therefore necessary to ensure the fiber an optimum

elasticity and a more efficient lubrication than that ensured by the batching oil.



It is therefore indispensable to have an efficient monitoring the lubrication oil

D7

1N

40

07

R4

44

.7K

+5

V

U9

MC

P2

55

11 2 3 4

5678T

XDV

SS

VD

DR

XD

VR

EF

CA

NL

CA

NH

RS

D9

1N41

48

R3

21

0K

R1

410

K

C1

70

.1uF

R4

21

0M

D13

1N

41

48

RE

SE

T

CU

RR

EN

T

R2

01

0K

C1

50

.1u

F

VO

LT

_Z

CD

R23

10

K

CU

RR

EN

T

C1

0.1

uF

R1

71

K

D5

1N

40

07

+1

2V

PG

C

+5V

C2

03

3pF

+5V

-12

V

LE

D

R1

21

K

R1

8

120

E

U1

0P

IC1

8F

248

0

9

18

19

20

1 2 3 4 5 6 7 82

12

22

32

42

52

62

72

8

10

11

12

13

14

15

16

17

OS

C1

/CLK

1/R

A7

RC

7/R

X/D

TV

SS

VD

D

MC

LR

/VP

P/R

E3

RA

0/A

N0

RA

1/A

N1

RA

2/A

N2

/VR

EF

-R

A3

/AN

3/V

RE

F+

RA

4/T

0C

KI

RA

5/A

N4

VS

SR

B0/

INT

0/A

N10

RB

1/I

NT1

/AN

8R

B2

/IN

T2/

CA

NT

XR

B3

/CA

NR

XR

B4

/KB

I0/A

N9

RB

5/K

BI1

/PG

MR

B6

/KB

I2/P

GC

RB

7/K

BI3

/PG

D

OS

C2

/CLK

O/R

A6

RC

0/T

1OS

SO

/T13

CK

IR

C1

/T1O

SI

RC

2/C

CP

1R

C3

/SC

K/S

CL

RC

4/S

DI/

SD

AR

C5

/SD

OR

C6/

TX/C

K

R2

515

0E

D1

LE

D

J9

CO

N2

1 2

-12

V

+C

610

uF

R4

110

K

R11

33

E

+5

V

VO

LTA

GE

-+

U1

0AL

M35

8

3 21

8 4

R1

51

0K

+

C2

41

000

uF

25

V

R3

64

.7K

RE

SE

T

- +

U1

ALM

358

321

84

R49

4.7

M

PT

J5

CO

N2

1 2

R6

20K

C5

0.1

uF

R1

10

K

RX

R4

51

KR

301

0K

R22

1K

R9

1K

C3

0.1u

F

+1

2V

D6

1N

40

07

C16

0.1u

F

D2

1N4

14

8

C2

60

.1uF

PT

Voltage

Sensor

+5V

-12V

R10

10

K

Y1

4M

Hz

+1

2V

R2

61

K

- +

U1

BL

M3

58

567

84

R2

910

K

+C

23

10

00u

F 2

5V

R4

34

.7K

LCD Display

+5V

LED

VO

LT_

ZC

D

R8

10K

Current

Sensor

Frequency

C2

0.1

uF

C1

80

.1u

FB

UZ

ZE

R

U5

781

2

13

2

VIN

VO

UT

GND

R7

10

K

R13

10k

R2

43

30E

C1

93

3pF

R2

1

330

E

+5

V

+5V

R4

10

K

J12

LC

D

1 2 3 4 5 6 7 8 9 10

11

12

13

14

15

16

C2

50

.1u

F

D4

1N

40

07

PG

D

- +

U3

ALM

358

321

84

J2

Bu

zze

r/H

utt

er

1 2

J1

CA

N B

us

1 2

Q1 BC

557

+5V

+5

V

C4

0.1

uF

CT

D8

1N4

14

8

+C

2210

uF

- +

U3

BL

M3

58

567

84

SW

1

RE

SE

T S

W

R2

81

0K

J4

PR

OG

1 2 3 4 5

TX

+5V

+1

2V

-12V

R3

1K

C2

10

.1u

F

D14

1N

41

48

R1

61

0K

VO

LTA

GE

CAN Interface

Power Supply

+5

V

+5

V

D3

1N41

48

+12

V

R2

71

K

J3

CO

N3

1 2 3

+5

V

U6

79

12

23

1

VIN

VO

UT

GND

-12

V

R19

10

0E

D10 LE

D

U7

78

05

13

2

VIN

VO

UT

GND

Fig. 4.9: Circuit Diagram of Motor Fault Collection Unit



tank’s condition with the help of its quantity and pressure of oil. The two main

parameters for oil to consider are oil level and pressure. The Fig. 4.10 is the

block diagram of oil tank fault collection unit. The congregated data from the

sensors are first amplified and applied to ADC channel of microcontroller. The

intelligent microcontroller calibrates the sensor data, display on local display

unit and the data collected is then transmitted over to Central Unit through

CAN bus for analysis of fault condition.

4.5.1 Oil Pressure Measurement

Mechanical methods of measuring pressure have been known for

centuries. The first pressure gauges used flexible elements as sensors. As

pressure changed, the flexible element moved and this motion was used to

rotate a pointer in front of a dial. In these mechanical pressure sensors, a

bourdon tube, a diaphragm, or a bellows element detected the process pressure

and caused a corresponding movement. A bourdon tube is C-shaped and has

an oval cross-section with one end of the tube connected to the process

Fig. 4.10: Block Diagram of Oil Tank Fault Collection

CAN Bus

Pressure Sensor

Microcontroller

Signal

Conditioning


CAN Transceiver

Level Sensor



pressure. The other end is sealed and connected to the pointer or transmitter

mechanism. To increase their sensitivity, Bourdon tube elements can be

extended into spirals or helical coils. This increases their effective angular

length and, therefore, increases the movement at their tip, which in turn

increases the resolution of the transducer [14]. Because of the inherent

limitations of mechanical motion-balance devices, first the force-balance and

later the solid state pressure transducer were introduced. The first unbonded-

wire strain gauges were introduced in the late 1930s. In this device, the wire

filament is attached to a structure under strain, and the resistance in the strained

wire is measured. This design was inherently unstable and could not maintain

calibration. Also there were problems with degradation of the bond between

the wire filament and the diaphragm, and with hysteresis caused by thermo

elastic strain in the wire [15]. The potentiometric pressure sensor provides a

simple method for obtaining an electronic output from a mechanical pressure

gauge. The device consists of a precision potentiometer, whose wiper arm is

mechanically linked to a Bourdon or bellows element. The movement of the

wiper arm across the potentiometer converts the mechanically detected sensor

deflection into a resistance measurement, using a Wheatstone bridge circuit

[15]. Potentiometric transducers can be made small and installed in very tight

quarters, such as inside the housing of a 4.5 in. dial pressure gauge. They also

provide an output that can be used without additional amplification. This

permits them to be used in low power applications. They are also inexpensive.

Potentiometric transducers can detect pressures between 5 and 10,000 psig (35

kPa to 70 MPa). Their accuracy is between 0.5% and 1% of full scale. The

resonant-wire pressure transducer was introduced in the late 1970. In this

design, a wire is gripped by a static member at one end and by the sensing

diaphragm at the other [16]. An oscillator circuit causes the wire to oscillate at

its resonant frequency. A change in process pressure changes the wire tension,

which in turn changes the resonant frequency of the wire. A digital counter

circuit detects the shift. Because this change in frequency can be detected quite



precisely, this type of transducer can be used for low differential pressure

applications as well as to detect absolute and gauge pressures. The most

significant advantage of the resonant wire pressure transducer is that it

generates an inherently digital signal, which can be sent directly to a stable

crystal clock in a microprocessor. Limitations include sensitivity to temperature

variation, a nonlinear output signal, and some sensitivity to shock and

vibration. The piezoresistive pressure sensor elements consist of a silicon chip

with an etched diaphragm and, a glass base anodically bonded to the silicon at

the wafer level. The front side of the chip contains four ion-implanted resistors

in a Wheatstone bridge configuration. The resistors are located on the silicon

membrane and metal paths provide electrical connections. When a pressure is

applied, the membrane deflects causing to change in resistance of

piezoresistors which results in unbalancing the bridge. Therefore voltage

developed across bridge is proportional to the applied pressure [17]. The

piezoresistive sensors have excellent electrical and mechanical stability that

can be fabricated in a very small size and hence been widely used for industrial

and biomedical electronics [18].

While selecting the pressure sensor in Textile Industry, good

repeatability often is more important with accuracy. If process pressures vary

over a wide range, transducers with good linearity and low hysteresis are the

preferred choice. Ambient and process temperature variations also cause errors

in pressure measurements, particularly in detecting low. In such applications,

temperature compensators must be used. Keller Series 21 MC sensor [19]

fulfills these requirements. These piezoresistive silicon pressure transmitters

are produced on the new Keller automatic brazing lines, making possible the

mass production of high quality pressure transmitters at low cost. This new

technology allows the crack free construction of the pressure port without using

seals or O-rings. In the brass sensor line (Series 21 MC), a steel insert and a

nickel diaphragm is brazed into brass housing. The header with the silicon

pressure sensor and glass lead through pins is welded to the steel insert



Fig. 4.11: Pressure Transmitter

underneath the oil filling. The tiny chip-on-board amplifier (weight ≈ 1 gram)

with the Keller-specific “PROGRES” circuit is mounted directly on the glass

feed-through pins. It is then encapsulated in silicone compound for humidity

and vibration protection.

The main features are as follows-

For Industrial applications

Compact version

Pressure range 5 Bars

Max overload pressure range 10 Bars

Output 4-20 mA

Operating temperature -25 to 80 oC

Accuracy 1% F.S. and

Sensitivity ± 0.04% /oC

4.5.2 Oil Level Measurement

There are different techniques for measure the level of oil. Some

techniques are available like magnetic principle based ultrasonic based and

resistive float type. The magnetic and ultrasonic sensors are somehow difficult

to mount with oil tank, therefore in oil tank unit the simple resistive type

sensors are selected here. The oil level sensor unit is nothing but a variable

resistor. The senor unit is positioned in the oil tank of the machine. The typical

float level sensor is shown in Fig. 4.12. It consists of a float, usually made of

foam, connected to a thin, metal rod. The end of the rod is mounted to a

variable resistor. In an oil tank, the variable resistor consists of a strip of

resistive material connected on one side to the ground. A wiper connected to

the gauge slides along this strip of material conducting the current from the

gauge to the resistor. The wiper slides up or down with the oil level in the tank

rising or falling respectively. The sensor unit operating nominally between 0

and100 corresponding to tank being Full or Empty. There are several ways

of capturing signal from sensor unit and convert it into an equivalent digital



code. With one approach, the small signal from sensor is amplified and

converted into digital code. When the resistance is at a certain point, it will also

turn on a "Low Level" indicator. When the tank level reaches to its top limit the

maximum current flows and the display unit indicates a “Full Level”.

The full circuit diagram of oil tank fault collection unit is shown in the

Fig. 4.13.

4.6 Other Fault Collection

There are several other fault conditions which can halt the production

line. Majority of them are of digital type which represents the different

mechanical position sensors, detection sensors, emergency stop buttons etc. In

case of weaving machine it is necessary to keep a keen eye on the every thread

which is crossing each other. Failure to detect the thread damage or thread

spool finish results in the downgraded cloth production. Optical sensors

Fig. 4.12: Float Level Sensor

Measure Height Floating Material

Free Movement

Mounting Metal Surface

R



provides a vital role with their ease of implementation, small size and fast

response and hence are first choice of selection in the detection process.

J4 PROG

1 2 3 4 5

+

C24

1000

uF 2

5V

R251

50E

D61N

4007

D1 LED

U10

PIC1

8F24

80

9

181920

1 2 3 4 5 6 7 82122232425262728

10 11 12 13 14151617

OSC1

/CLK

1/RA

7

RC7/

RX/D

TVS

SVD

D

MCLR

/VPP

/RE3

RA0/A

N0RA

1/AN1

RA2/A

N2/V

REF-

RA3/A

N3/V

REF+

RA4/T

0CKI

RA5/A

N4VS

SRB

0/IN

T0/A

N10

RB1/

INT1

/AN8

RB2/

INT2

/CAN

TXRB

3/CA

NRX

RB4/

KBI0/

AN9

RB5/

KBI1

/PGM

RB6/

KBI2

/PGC

RB7/

KBI3

/PGD

OSC2

/CLK

O/RA

6RC

0/T1

OSSO

/T13

CKI

RC1/

T1OS

IRC

2/CC

P1RC

3/SC

K/SC

LRC

4/SD

I/SDA

RC5/

SDO

RC6/T

X/CK

C4 0.1u

F

C15

0.1uF

+C2

310

00uF

25V

R22

1K

Pres

sure S

enso

r

+5V

R24

330E

Power

Supply

PGC

C3 0.1uF

R18

120E

+5V

-+U2

B

LM35

8

5 67

8 4

J12

LCD

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

D10 LED

D51N

4007

D71N

4007

Q1 BC55

7

+5V

LED

C10

0.1u

F

+5V

R11

33E

J1

CAN

Bus

1 2LE

D

R13

10k

C12

0.1uF

-+U4

B

LM35

8

5 67

8 4C8 0.

1uF

+12V

+5V

Leve

l

R6 20K

C19

33pF

LCD

Disp

lay

J3CO

N3

1 2 3

+5V

+5V

+5V

+5V

Pres

sure

Sen

sor

1 2 3

R21

330E

CAN In

terf

ace

+5V

RESE

T

Level Se

nsor

RESE

T

+5V

C17

0.1uF

TX

U679

12

23

1

VIN

VOUT

GND

U778

05

13

2

VIN

VOUT

GND

Leve

l

+5V

Leve

l Sen

sor

1 2 3

RXPGD

+5V

D41N

4007

C13

0.1u

F

C16

0.1u

F

+5V

C20

33pF

J2

Buzze

r/Hutt

er

1 2

Y1 4MHz

-12V

U9MC

P255

11 2 3 4

5678TX

DVS

SVD

DRX

DVR

EFCA

NLCA

NHRS

R5 250E

U578

12

13

2

VIN

VOUT

GND

C18

0.1u

F

SW1

RESE

T SW

BUZZ

ER

Fig. 4.13: Circuit Diagram of Oil Tank Fault Collection Unit



Several optical sensors with some mechanical arrangements are implemented

on the machine to detect the fault or safe states. In fully electronic controlled

machine a reference starting position call home position is marked and can be

checked frequently before starting the new operation. Failing to reach at home

position can alter the reference point and hence the overall program positions.

Some of the faults can be treated as on the highest priority faults and

needs to be resolved very quickly. Some emergency breaking systems or

emergency switches are also provided on the machine to stop the operation on

any critical circumstances and needs immediate attention. These are also

considered as faults and having strong appeal in defining the machine health.

Frequent emergency stops show the poor performance of the machine or the

machine operator.

CAN Bus

Optical Sensor

Microcontroller

Signal

Conditioning


CAN Transceiver

Digital Sensor

Digital Fault

Signal

Conditioning Digital Fault

Fig. 4.14: Block Diagram of Other Fault collection



4.6.1 Optical Sensor

Fig. 4.16: Yarn Break Detection (Optical) Sensor [20]

Fig. 4.15: Stop mechanism with optical sensor; (a) Work Position, (b) Yarn Breakage Position, (c) Out Position

Light beam

(c)

(a)

(b)



Warping is aimed at preparing the weaver’s beam to be set up on the

weaving machine. Moreover the warper systems are equipped with yarn

breakage monitoring systems with optical sensor as shown in Fig. 4.15. During

warping the thread supports the drop pin and the light beam are not interrupted

(Fig. 4.15a). At thread breaking or marked thread loosening, the drop pin,

being no longer supported hence rotates and shades the light beam (Fig. 4.15b).

The idle threads are cut by pushing the relevant keys: the drop pins take up a

position which does not interrupt the light beam, thus enabling the working of

all other threads (Fig. 4.15c). The actual sensor array used for detection of yarn

breakage is shown in the Fig. 4.16.

The detailed circuit diagram of digital fault collection unit is shown in

the Fig. 4.17. The circuit consists of the arrangement for the attachment of

sensors of various operating voltage range of 3V to 30V. The inputs from these

sensors are optically isolated so as to protect the digital sensing logic and the

controller. The system has its own power supply built on it and the local

display for the purpose of debugging and indication of sensor states. The

system updates sensor states to the control unit through the CAN

communication bus. The algorithm of the sensing system is shown in the Fig.

4.18.

The software algorithm of the sensor units for analog as well as digital

fault sensing is similar. There is a constant cycle of reading the fault

information from the various sensors and converting them to the user

understandable form by calibrating the binary data to the standard measurement

units. These converted measurements of various parameters are then sent

periodically to the central unit for the analysis process. In case of emergency

faults the system flow skips the wait period and transfers the fault data

immediately to the central unit. Otherwise the cycle keeps on repeating the

same process and runs as long as the machine is functioning.



Fig. 4.17: Circuit Diagram of Digital Fault Collection Unit

+

C24

1000

uF 2

5V

U10

PIC1

8F24

80

9

181920

1 2 3 4 5 6 7 82122232425262728

10 11 12 13 14151617

OSC

1/C

LK1/

RA7

RC7/

RX/

DT

VSS

VDD

MC

LR/V

PP/R

E3R

A0/A

N0

RA1

/AN

1R

A2/A

N2/

VREF

-R

A3/A

N3/

VREF

+R

A4/T

0CKI

RA5

/AN

4VS

SR

B0/IN

T0/A

N10

RB1

/INT1

/AN

8R

B2/IN

T2/C

ANTX

RB3

/CAN

RX

RB4

/KBI

0/AN

9R

B5/K

BI1/

PGM

RB6

/KBI

2/PG

CR

B7/K

BI3/

PGD

OSC

2/C

LKO

/RA6

RC

0/T1

OSSO

/T13

CKI

RC

1/T1

OSI

RC

2/C

CP1

RC

3/SC

K/SC

LR

C4/S

DI/S

DA

RC

5/SD

ORC

6/TX

/CK

Opti

cal

Sensor

U8

MCT

2E

16

2

5 4

Sens

orB

C18

0.1u

F

D1

LED

J11

Sens

or

1 2 3

C17

0.1u

F

C16

0.1u

F

+5V

R25

150E

+5V

Y1

4MH

z

R31

330E

R18

120E

U8

MCT

2E

16

2

5 4

U6

7912

23

1

VIN

VOU

T

GND

R6 20K

C3

0.1u

F

D4

1N40

07

R21

330E

R2 10

K

J3C

ON

3

1 2 3

J12

LCD

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

C20

33pF

U8

MCT

2E

16

2

5 4+

C23

1000

uF 2

5V

Sens

orC

U7

7805

13

2

VIN

VOUT

GND

R22

1K

+5V

SW1

RES

ET S

W

R13

10k

+5V

+5V

+5V

J2

Buzz

er/H

utte

r

1 2

R31

330E

+5V

LCD

Displa

y

R11

33E

J11

Sens

or

1 2 3

D10 LE

D

U9

MC

P255

11 2 3 4

5678TX

DVS

SVD

DR

XDVR

EFC

ANL

CAN

HRS

+5V

U5

7812

13

2

VIN

VOU

T

GND

J1

CAN

Bus

1 2

D7

1N40

07

PGD

+5V

+12V

Q1 BC

557

+5V

RES

ET

R31

330E

Opti

cal

Sensor

R2 10

K

D5

1N40

07

RESE

T

+5V

C15

0.1u

F

C4

0.1u

F

+5V

+5V

J4 PROG

1 2 3 4 5

LED

+5V

CAN

Interf

ace

Sens

orB

-12V

Powe

r Supp

ly

Sens

orC

LED

C19

33pF

+5V

R2 10

K

Opti

cal

Sensor

D6

1N40

07

+5V

R24

330E

PGC

J11

Sens

or

1 2 3

BUZZ

ER



Hardware Initialization Parameter Scan Time Initialization

Start

CAN Communication Setting Initialization

Read Machine Digital Parameter

Read Machine Analog Parameter

Calibrate and store Machine Parameters

Is Emergency

Fault?

Is Scan Time Over?

Send Parameters to Central Node

Restart Scan Timer

Yes

No

No

Yes

Fig. 4.18 Flowchart of the Sensor Unit



4.7 The Central Unit

4.7.1 Block diagram

The block diagram of Central unit is shown in Fig. 4.19. The

microcontroller is main intelligent device from this unit. The CAN transceiver

is used for CAN bus communication. The LCD is used for display the sensor

parameters like temperature, pressure etc. The RS232 interface is for PC serial

COM port interface. The all sensor parameters are sent through the RS232

interface for further process diagnosis.

As shown in the Fig. 4.20 the Central unit consists of a PIC18F2480

microcontroller with a built-in CAN module and MCP2551 transceiver chip.

The microcontroller is operated from 4MHz crystal. The MCLR input is

connected to an external reset button. The CAN outputs (RB2/CANTX and

RB3/CANRX) of the microcontroller are connected to the Txd and Rxd inputs

of the MCP2551. Pins CANH and CANL of the transceiver chip are connected

CAN Bus

Fig. 4.19: Block Diagram of Central unit

Microcontroller

Serial RS232

Interface

Faulty Machine Indicator Panel

CAN Transceiver

Buzzer Or Hooter



to the CAN bus. LCD16X2 is connected to PORTC of the microcontroller to

display the sensor parameters. Fig. 4.21 shows the process flowchart of the

PGD

J2PRO

G

12345

R24

120E

+5V

C24

0.1uF

+C

271000uF 25V

LED

U11

MAX232A

1345

161526

129 1110 13

8

14

7

C1+

C1-

C2+

C2-

VCC

GN

DV+V-

R1O

UT

R2O

UT

T1INT2IN

R1IN

R2IN

T1OU

T

T2OU

T

+5V

R22

330E

BUZZER

RX

+5V

Power Supply

PGC

U10

PIC18F2480

9

18 19 20

1234567821 22 23 24 25 26 27 28

101112131415 16 17

OSC

1/CLK1/R

A7

RC

7/RX/D

TVSSVD

D

MC

LR/VPP/R

E3R

A0/AN0

RA1/AN

1R

A2/AN2/VR

EF-R

A3/AN3/VR

EF+R

A4/T0CKI

RA5/AN

4VSS

RB0/IN

T0/AN10

RB1/IN

T1/AN8

RB2/IN

T2/CAN

TXR

B3/CAN

RX

RB4/KBI0/AN

9R

B5/KBI1/PGM

RB6/KBI2/PG

CR

B7/KBI3/PGD

OSC

2/CLKO

/RA6

RC

0/T1OSSO

/T13CKI

RC

1/T1OSI

RC

2/CC

P1R

C3/SC

K/SCL

RC

4/SDI/SD

AR

C5/SD

OR

C6/TX/C

K

+5V

D1

LED

C20

0.1uF

+5V

+C

1810uF

R26

330E

+5V

C25

33pF

CAN InterfaceJ1

CAN

Bus

12+5V

R2

33E

R21

10k

+5V

C23

0.1uF

J10

Buzzer/Hutter

12

LED

J4

Transformer

123

Y1

4MH

z

R27

1K

U7

7805

13

2

VINVO

UT

GND

RX

D1LED

U2

MC

P25511234

5 6 7 8TXDVSSVD

DR

XDVR

EFC

ANL

CAN

H RS

D4

1N4007

+5V

+5V

C21

0.1uF

D7

1N4007 R

12

20K

+C

16

10uF

Personal Computer

RESET

+5V

TX

RESET

SW1

RESET SW

+

C19

10uF

TX

Interface

+

C17

10uF

D5

1N4007

+5V

C28

33pF

Q1BC

557

D6

1N4007

C15

0.1uF

R33

150E

P1

PC

5 9 4 8 3 7 2 6 1

1011

LCD Display

J7LCD

12345678910111213141516

Fig. 4.20: Circuit Diagram of Central Unit



central node which gathers the fault data from various sensing nodes and passes

them to the PC.

4.8 CAN Node

For CAN-bus based designs, it is easier to use any microcontroller with

a built-in CAN module. PIC, ARM, AVR are the popular microcontrollers

having built-in CAN module. As shown in Fig. 4.22, such devices include

Fig. 4.21 Flowchart of the Central Unit

Hardware Initialization Serial Communication Initialization

Start

CAN Communication Setting Initialization

Wait for Fault Information

Is Emergency

Fault?

Is Fault info received?

Store data to FIFO queue

Send Data to PC

Yes

No

Yes



built-in CAN controller hardware on the PIC microcontroller. All that required

to make a CAN node is to add a CAN transceiver chip.

Communication between CAN Nodes

The following is a simple two-node CAN bus communication. The

block diagram is shown in Fig. 4.23. The system is made up of two CAN

nodes. One node (called Central node) requests to another node after certain

interval like second and displays the received parameters on an LCD. This

process is repeated continuously. Central node sends all parameters to Personal

PIC 18F2480

Microcontroller & CAN Controller

module

CAN Transceiver MCP2551

CAN Bus

Rx

Tx

CAN Node

Fig. 4.22: CAN node with integrated CAN module

Fig. 4.23: Block diagram of the CAN Communication

PICMicro-

controller

PICMicro-

controller

SENSOR DISPLAY

CANTransceiver

CANTransceiver



Computer for further analysis. Personal Computer is having fuzzy diagnosis

system. The other node (called SENSOR node) reads the pressure and

proximity from an external pressure sensor and proximity sensor respectively.

If any major deviations or any fault occurs SENSOR node sends the parameters

to Central node through CAN bus immediately.

4.8.1 CAN Transceiver MCP2551

The MCP2551 CAN transceiver [28] from Microchip is interfaced with

PIC18F2480. Typically, each node in a CAN system must have a device to

convert the digital signals generated by a CAN controller to signals suitable for

transmission over the bus cabling (differential output). It also provides a buffer

between the CAN controller and the high-voltage spikes that can be generated

on the CAN bus by outside sources (EMI, ESD, electrical transients, etc.).The

MCP2551 is a high-speed CAN, fault-tolerant device that serves as the

interface between a CAN protocol controller and the physical bus. The

MCP2551 provides differential transmit and receive capability for the CAN

protocol controller and is fully compatible with the ISO-11898 standard,

including 24V requirements. It will operate at speeds of up to 1 Mb/s.

The CAN module uses port pin 24 RB3/CANRX and port pin 23 RB2/CANTX

for CAN bus receive and transmit functions respectively. These pins are

connected to the CAN bus via an MCP2551-type CAN bus transceiver chip.

CAN InterfaceU2 MCP2551

1234 5

678TXD

VSSVDDRXD VREF

CANLCANH

RS

J1

CAN Bus

12

+5V

C240.1uF

C210.1uF

R33 150E

+5V

PIC18F2480

1819202122232425262728

151617RC7/RX/DT

VSSVDD

RB0/INT0/AN10RB1/INT1/AN8

RB2/INT2/CANTXRB3/CANRX

RB4/KBI0/AN9RB5/KBI1/PGMRB6/KBI2/PGCRB7/KBI3/PGD

RC4/SDI/SDARC5/SDO

RC6/TX/CK

R24

120EC23

0.1uF

Fig. 4.24: Interfacing Microcontroller with MCP2551



The circuit diagram of CAN Node is given in Fig. 4.25. Two CAN

-12V

C17

0.1uF

CAN NODE1

TX

BUZZER

- +U

4A

LM358

321

84

+5V

Q1BC557

+5V

+5V

P1

PC

5 9 4 8 3 7 2 6 1

1 011

C4

0.1uF

R9

1K

SW1

RESET SW

U7

7805

13

2

VINVO

UT

GN D

R24

120E

U9

MCP2551

12345 6 7 8

TXDVSSVDDR

XDVR

EFC

ANLCAN

H RS

BUZZER

J4

Transformer

123

- +U2A

LM358

321

84

R12

1K

J11

Proximity Sensor

123

R29

10K

R1

10K

R18

120E

R2

33E

C28

33pF

-+

U3B

LM358

5 67

8 4

C12

0.1uF

R26

1K

R620K

Level SensorR

3010K

Y1

4MH

z

+12V

D9

1N4148

C21

0.1uF

+12V

LED

C1933pF

R21

10k

R22

330E

C25

33pF

J12

LCD

12345678910111213141516

+C

231000uF 25V

+5V

C200.1uF

-+

U3A

LM358

3 21

8 4

C16

0.1uF

LED

R27

1K

C1

0.1uF

+5V

RX

R3210K

CAN NODE2

R26

330E

C210.1uF

R25150E

-12V

D7

1N4007

R210K

Level Sensor

123

+5V

LED

D6

1N4007

+5V

U8MCT2E

16

2

54

C23

0.1uF

D6

1N4007 Humidity Sensor

+12V

C15

0.1uF

Power Supply

+5V

U2M

CP25511234

5 6 7 8TXDVSSVDDRXD

VREF

CANL

CAN

H RS

R21

330E

Level

C150.1uF

Temperature

J1

CAN Bus

12

D5

1N4007

+5V

J2PROG

12345

-12V

PGC

D5

1N4007

J2

Buzzer/Hutter

12

+

C24

1000uF 25V

U10

PIC18F2480

9

18 19 20

1234567821 22 23 24 25 26 27 28

101112131415 16 17

OSC1/CLK1/RA7

RC7/RX/DT

VSSVD

D

MC

LR/VPP/RE3R

A0/AN0

RA1/AN

1R

A2/AN2/VR

EF-R

A3/AN3/VR

EF+R

A4/T0CKI

RA5/AN

4VSS

RB0/INT0/AN10R

B1/INT1/AN8RB2/IN

T2/CANTX

RB3/CANRX

RB4/KBI0/AN9

RB5/KBI1/PGM

RB6/KBI2/PGC

RB7/KBI3/PGD

OSC2/CLKO

/RA6

RC

0/T1OSSO

/T13CKIR

C1/T1O

SIR

C2/C

CP1R

C3/SCK/SCL

RC4/SDI/SD

AR

C5/SD

ORC

6/TX/CK

Power Supply

+5V

+12V

+5V

R11

33E

+5V

+5VLevel

U10

PIC18F2480

9

18 19 20

1234567821 22 23 24 25 26 27 28

101112131415 16 17

OSC1/CLK1/RA7

RC7/R

X/DTVSSVD

D

MCLR

/VPP/RE3

RA0/AN

0R

A1/AN1

RA2/AN

2/VREF-R

A3/AN3/VREF+

RA4/T0C

KIR

A5/AN4

VSSR

B0/INT0/AN10R

B1/INT1/AN8RB2/IN

T2/CANTX

RB3/CAN

RXR

B4/KBI0/AN9RB5/KBI1/PG

MRB6/KBI2/PG

CRB7/KBI3/PG

D

OSC2/CLKO

/RA6

RC0/T1O

SSO/T13C

KIR

C1/T1OSI

RC2/CC

P1R

C3/SCK/SCL

RC4/SD

I/SDAR

C5/SD

ORC

6/TX/CKJ7LCD

12345678910111213141516

D4

1N4007

J5CO

N2 12

D1LED

+C2210uF

VOLTAG

E

+5V

R5

250E

-12V

C5

0.1uF

C30.1uF

R14

10K

Pressure Sensor

123

TX

R31

330E

R24330E

+5V

C20

33pF

D3

1N4148

R17

1K

Personal Computer

Pressure Sensor

+

C19

10uF

R7

10K

Voltage Sensor

J3C

ON3

123

+12V

-+

U1B

LM358

5 67

8 4

C8

0.1uF

U11

MAX232A

1345

161526

129 1110 13

8

14

7

C1+

C1-C2+C2-

VCCG

NDV+V-

R1OU

T

R2OU

T

T1INT2IN

R1IN

R2IN

T1OUT

T2OUT

D1

LED

R4

10K

PGD

Humidity Sensor

123

Interface

+5V

RESET

C110.1uF

+5V

+5V

+5V

+5V

+C

271000uF 25V

R13

120E

Temperature

J4PROG

12345

D1LED

D4

1N4007

-12V

Hum

idity

R1610K

CAN Interface

+5V

R12

20K

D81N4148

- +U

4B

LM358

567

84

+5V

C10

0.1uF

LCD Display

D21N4148

Y1

4MHz

+5V

Temperature Sensor

RESET

CUR

RENT

Humidity

J9CO

N2 12

Temperature Sensor

123

Optical Sensor

+5V

R27

1K

U77805

13

2

VINVOU

T

G ND

Q1BC557

CUR

RENT

D7

1N4007

C14

0.1uF

R22

1K

R10

10K

+5V

SW1

RESET SW

+5V

TX

R19100E

PGC

RX

R15

10K

R2810K

RX

LED

R31K

VOLTAG

E

R13

10k

+5V

+C

16

10uF

R2010K

- +U2B

LM358

567

84

CT

C180.1uF

+C1810uF

LCD Display

+5V

PGD

C13

0.1uF

J1

CAN Bus

12

C2

0.1uF

CAN Interface

+5V

R33150E

R8

10K

C9

0.1uF

R23

10K

RESET

J10

Buzzer/Hutter

12

C7

0.1uF

U6

7912

23

1

VINVOU

T

GND

PT

RESET

CurrentSensor

+5V

+5V

R16

120E

+C610uF

-+

U1A

LM358

3 21

8 4

+5V

C24

0.1uF

D10LED

U5

7812

13

2

VINVOU

T

G ND

+

C17

10uF

Fig. 4.25: Circuit diagram of the CAN Communication between two different nodes



nodes are connected together using a twisted pair cable, terminated with a 120-

ohm resistor at each end. Both nodes are controlled by intelligent device

microcontroller PIC18F2480 [21]. Microcontroller is having inbuilt CAN

controller, so no external CAN controller is needed.

4.9 Laboratory Work

The experimental setup for Motor parameter measurement is shown in

Fig. 4.26 and Fig. 4.27. The experimental setup includes the embedded circuit

board which is made from PIC18F2480 having inbuilt CAN controller, power

supply section, signal conditioning for Current transformer (CT) and three

phase motor of 440 V, 1 Amp. The CT used is of 30/30mA specification. CT is

specially used for measuring the current of motor because it gives total

isolation. Each phase R, Y and B are attached with individual CT for current

measurement. The voltage transformers are used to monitor the present

voltages of the respective phases. The line frequency of the supply is monitored

using the zero crossing detector circuit.

Fig. 4.26: Experimental setup for Measurement of Motor Parameters



With this experimental setup we generated some faulty conditions those

can occur in the real time environment. The faults such as single phasing,

overload and low and high voltage were tested with the FIS. The results are

shown in the results section (Chapter V).

4.10 Graphical User Interface (GUI)

The success of any system mainly depends upon easiness in the

operation and clear understanding of it to the system operator. To ease the

handling of different fault conditions and to follow the respective remedies

Fig. 4.27: Experimental System Test setup



suggested by the system to the operator we have designed a GUI of the total

system. It is divided into several screens depending upon the different sections

of the system. The main front end navigation GUI is shown in the Fig. 4.28

from where user can access every section of the system. GUI has been designed

in MATLAB [23-25] software.

4.10.1 GUI for Weaving Section

Weaving section shows summery of two different parts - first is the

Machine health Determination and second - the Machine Environment

Determination. Machine health determination section includes Motor

Condition, Lubricant Oil Tank Condition and Emergency Faults Detection. The

Fig. 4.28: GUI Main window



detailed parameters generated by the FIS models from the data acquired can be

seen in the individual views.

4.10.2 GUI for Motor Condition Determination

The Fig. 4.30 shows the GUI window of Motor Condition determination. The

motor parameters such as Phase Currents, Phase Voltages and the operating

frequencies are continuously monitored. The motor condition depends mainly

on stator current of motor. The GUI also indicates the present motor health

condition. On any uneven change in rated parameter the system shows the

possible causes of the problem occurred and also the available remedy there

upon. The motor conditions like ‘Overloaded’, ‘Critically Overloaded’, and

Fig. 4.29: GUI of Weaving Section



‘Open Phase’ etc. can be seen in the Cause window which aids the operator to

quickly understand the underlying problem.

4.10.3 GUI for Environment Condition Determination

The Fig. 4.31 shows the GUI window of Environment Condition

determination. The environmental parameters like Humidity and Temperature

play a vital role in the quality production and in the smooth operation of the

machine. The machine health is also depends on the correct operating

conditions and failing to maintain can cause frequent breakdowns to the

machine and hence hamper the production process. The GUI includes the

present state of environment, temperature in degree Celsius, humidity in %rh,

and possible causes of fault if any. The Environment State ‘Good’ is always

expected for smooth operation.

Fig. 4.30: GUI of Motor Condition



4.10.4 GUI for Lubrication Oil Tank Condition Determination

To keep the machine running smoother it requires the frequent

lubrication. In case of high speed machine those are presently running in the

Textile Industry needs a continuous oil circulation for the lubrication and

cooling of several frictional parts. The constantly pressurized oil supply hence

installed with every machine and the pressure and quantity of the oil needs to

be monitored continuously. The Fig. 4.32 shows the GUI window of Oil tank

Condition determination where the oil pressure and Oil level/Quantity are

measured and displayed. The possible faults such ac low oil pressure and low

oil levels are continually monitored for any failure pertaining to tank condition.

Fig. 4.31: GUI of Environment Condition



4.10.5 GUI for Emergency Fault Condition Determination

There are several sensors installed in the machine for the proper working

of each segment of the machine and to get the present state of the machine

operations. These sensors can be mechanical, electromechanical or optical. It is

very necessary to keep these sensors functioning all the time to get reliable

operation of the machine. The failure of these sensors is considered as machine

fault and their weightage is decided according to their function and

consequence on the particular machine. There are some optional buttons also

provided to stop the machine immediately on the serious events. These buttons

have highest priority and marked as serious faults to get the immediate

attention. The Fig. 4.33 shows the GUI window of Emergency Faults.

Fig. 4.32: GUI of Oil Tank condition



4.11 Controller Area Network (CAN)

The Controller Area Network (CAN) is a serial bus communications

protocol developed by Bosch (an electrical equipment manufacturer in

Germany) in the early 1980s. Thereafter CAN was standardized as ISO-11898

and ISO-11519, establishing itself as the standard protocol for in-vehicle

networking in the auto industry [26]. In the early days of the automotive

industry, localized stand-alone controllers had been used to manage various

actuators and electromechanical subsystems. By networking the Electronics in

vehicles with CAN, however, these subsystems could be controlled from a

central point- the engine control unit (ECU) thus increasing functionality,

adding modularity and making diagnostic processes more efficient.

Fig. 4.33: GUI of Emergency Faults



Early CAN development was mainly supported by the vehicle industry,

as it was used in passenger cars, boats, trucks, and other types of vehicles.

Today the CAN protocol is used in many other fields in applications that call

for networked embedded control including industrial automation, medical

applications, building automation, weaving machines, and production

machinery. CAN offer an efficient communication protocol between sensors,

actuators, controllers, and other nodes in real-time applications, and is known

for its simplicity, reliability, and high performance.

The CAN protocol is based on a bus topology, and only two wires are

needed for communication over a CAN bus. The bus has a multimaster

structure where each device on the bus can send or receive data. Only one

device can send data at any time while all the others listen. If two or more

devices attempt to send data at the same time the one with the highest priority

is allowed to send its data while the others return to receive mode.

The CAN protocol is based on CSMA/CD+AMP (Carrier-Sense

Multiple Access/Collision Detection with Arbitration on Message Priority)

protocol, which is similar to the protocol used in Ethernet LAN. When Ethernet

detects a collision, the sending nodes simply stop transmitting and wait a

random amount of time before trying to send again. CAN protocol, however,

solve the collision problem using the principle of arbitration, where only the

highest priority node is given the right to send its data [27].

4.11.1 Message frames in CAN

To communicate between different nodes of the system the CAN

communication bus is implemented which provide better noise immunity to the

industrial noise and transfers the data at very high data rates. The

communication between the central node and the fault collection node happens

in the form of frames. The list of frames used in the communication and their

priory on the CAN bus is listed in the Table 4.2.



Table 4.2 CAN Communication Frames

Sr .No. Frame Description Frame Length Priority

1 Emergency Fault 8 Byte 1

2 Warp/Weft Break 8 Byte 2

3 Motor Overload 8 Byte 3

4 Motor Single Phase 8 Byte 4

5 Oil Pressure Low 8 Byte 5

6 Humidity Level Low 8 Byte 6

7 Humidifier Failure 8 Byte 7

9 Temperature High 8 Byte 9

10 Temperature Low 8 Byte 10

11 Motor Voltage Change 8 Byte 11

12 Motor Frequency Change 8 Byte 12

13 Oil Level Low 8 Byte 13



4.12 References

1. Prade H. and Negoita C. V, (eds.), Fuzzy Logic in Knowledge

Engineering. Verlag TUV Rheinland, Koln, 1986.

2. National Semiconductor, LM35 Temperature Sensor Datasheet.

3. N. M. White and J. D. Turner, Thick film sensors: past, present and

future, Measur. Sci. Technol, 8: pp. 1-20, 1997.

4. Laville C, Pellet C, Interdigitated humidity sensors for a portable

clinical microsystem, IEEE Trans Biomed Eng 49: pp. 1162–1167,

2002.

5. Humidity Sensor Module SY-HS-220 Datasheet.

6. M. Peltola, Slip of ac induction motors and how to minimize it, ABB

Drives Press Releases Technical Paper, ABB, New Berlin, 2003, pp. 1–

7.

7. A. Patel and M. Ferdowsi, Advanced Current Sensing Techniques for

Power Electronic Converters, IEEE Vehicular Power and Propulsion

Conference, Arlington, Texas, September 2007.

8. D. Ward and J. Exon, Experience with using Rogowski coils for

transient measurements, IEE Colloquium on Pulsed Power Technology,

pp. 6/1-6/4, 20 February 1992.

9. D. Ward and J. Exon, Using Rogowski coils for transient current

measurements, Engineering Science and Education Journal. (Last

visited: 7th November 2007).

10. G. Xiaohua, Y. Miaoyuan, X. Yan, Z. Mingjun, and L. Jingsheng,

Rogowski current transducers suit relay protection and measurement, in

IEEE International Conference on Power System Technology, 13-17

October 2002, vol.4, pp. 2617-2621.

11. Instrument Transformers, A Reference Manual, Kappa Electricals,

Madras, India, 1996. 12. A. Phadke, J. Thorp, and M. Adamiak, A new measurement technique

for tracking voltage phasors, local systems frequency, and rate of



change of frequency, IEEE Trans. Power Application System, vol. PAS-

102, pp. 1025-1038, May 1983.

13. Paul Horowitz and Winfield Hill, The art of electronics, 2nd Ed,

Cambridge University Press, 1989, ISBN 0 521 37095 7, pp.579.

14. Richard S. Figliola, Donald E. Beasley, Theory and Design for

Mechanical Measurements, 1991.

15. The Pressure, Strain, and Force Handbook, Omega Press LLC, 1996.

16. Marks' Standard Handbook for Mechanical Engineers (10th Edition)

Edited by Avallone, E.A., Baumeister, T., McGraw-Hill, 1996.

17. S. Sugiyama, M. Takigawa and I. Igarashi, Integrated piezoresistive

pressure sensor with both voltage and frequency output, Sensors and

Actuators A, 4: pp. 113-120, 1983.

18. W. H. Ko, J. Hynecek, and S. F. Boettcher, Development of a miniature

pressure transducer for biomedical application, IEEE Trans. Electronic

Devices, 1979.

19. www.keller-druck.com (visited May 2008)

20. Giovanni Castelli, Salvatore Maietta, Giuseppe Sigrisi, Ivo Matteo

Slaviero, Reference books of textile technology: weaving, ACIMIT,

October 2000.

21. PIC18F2480 High speed microcontroller Datasheet, Microchip

Technology, Inc.

22. V. V. Terzija, B. M. Djuric, and B. Kovaccevic, Voltage phasor and

local system frequency estimation using Newton type algorithm, IEEE

Trans. Power Delivery, vol. 9, pp. 1358-1374, July 1994.

23. Brian R., Hunt Ronald L., Lipsman Jonathan M., Rosenberg, A Guide to

MATLAB for Beginners and Experienced Users, Cambridge University

Press.

24. Misza Kalechman, Practical MATLAB Applications for Engineers, CRC

Press.

25. Getting started with Matlab – The MathworksTM



26. www.can-cia.de, Homepage of the organization CAN in Automation

(CiA), 2004.

27. CAN specification version 2.0, Robert Bosch GmbH, Stuttgart,

Germany, 1991.

28. MCP2551 Data Sheet, High Speed CAN Transceiver, DS21667,

Microchip Technology, Inc.

chapter 4 hardware implementation of hardware...

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