condition monitoring through non destructive technique seminar
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ABSTRACT
Condition monitoring of components and plants are of great importance for safe
and reliable operation and for increasing productivity of plants. The challenges towards
the condition monitoring can be successfully met by employing non-destructive
evaluation (NDE) techniques. Vibration monitoring techniques are applied for periodic /
continuous assessment of machinery parts and plants. Acoustic emission technique is
used for leak detection and for structural integrity monitoring applications. Infrared
thermographs are employed for condition monitoring applications in steel, electrical and
petrochemical industries. Lubricant analysis by ferrography, and filed signature
mapping are also used for condition monitoring applications. Here, applications of these
NDE techniques could help to properly diagnose faults in plants components, enables
taking timely decision about repair / replacement of components / plants, thus ensuring
increased safety, reliability and productivity.
INTRODUCTION
The successful operation of structures / components during their entire life
requires the implementation of a dedicated programme for condition assessment through
in-service inspection (ISI) of all critical components of the plants / structures. The
condition assessment through ISI and life prediction approaches enable uninterrupted
operation, avoidance of unplanned shutdowns and taking decision on repair, up-
gradation, modernization and replacement of necessary components for extension of the
overall life of plants beyond their design lives. This is achieved through meticulous
planning and incorporation of non-destructive evaluation (NDE) techniques which aims
at detection and characterization of defects, stresses, corrosion micro structural
degradations and dimensional changes that occur in components during service life, due
to exposure to high temperature, pressure, static and dynamic loads, hostile environment
etc.
1. SIGNATURE ANALYSIS
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ness etc . . . . Condition assessment of plants through vibration analysis is a very
important method in spite of relatively higher initial cost of instruments. Acoustic
Emission Technique (AET) is an advanced technique for real time monitoring
application. An AE transducer or sensor acoustically coupled to a sample detects elastic
(Acoustic) energy emitted by the sample and gives information about the dynamic
changes taking place in the sample. AET is widely used for assessing structural integrity
of critical components, such as pressure vessels, pipe line, storage vessels and gas
cylinders. Infra red thermography (IR) is the mapping of IR radiations arising from the
natural or stimulated thermal radiations of an object and can be used for online
monitoring applications. Lubrication monitoring is carried out at periodic intervals to
identify the condition for the lubricant and to access the likely damages to the
machinery parts, through debris analysis by ferrography and quality assessment of
lubricants. More recently for condition monitoring and life extension problems, a new
dimension has been added to the existing NDE approaches with the availability and
adoption of procedure like field signature mapping.
1. VIBRATION MONITORING TECHNIQUES
Vibration is referred to as oscillation of an object about some equilibrium point.
VB monitoring technique has gained wide interest and acceptance for condition
monitoring applications. This is based on exciting vibrations in component by local
external impact or recording the vibration generated in a components under operating
conditions the most common source of vibration are gear gear-mesh, vane passing ,
rotor imbalance, misalignment, eccentricity, damaged bearings or gears, loose
components, rubbing components ,bend shafts, cavitations.
Vibration of a machinery is accessed with a help of transducers by measuring
the amplitude of vibration in terms of their parameters i.e. displacement velocity and
acceleration.
1.1 VIBRATION MONITORING INSTUMENTATION
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Following figure shows a measuring and analysis system that may be used for
monitoring the vibration signals from machines.
Following table gives general guide lines for identifying the causes of vibrations.
The relation between the fault and frequency, amplitude and direction of vibration, are
given. This is a useful guide for pin-pointing the cause in case vibration levels at certain
frequency are seen to increase.
Sl.
No FAULT FREQUENCY
DIRECTION OF
VIBRATION
1. ROTATING UNBALANCE SAME AS RUNNING SPEED RADIAL
2. MISALIGNMENT OF
BEARINGS
2*SPEED RADIAL AND AXIAL
3. ROLLER BEARING DEFECT
AT BALL OR ROLLER SPEEED
ULTRA SONIC FREQUENCIES (20-
60KHZ)
RADIAL AND AXIAL
4.
OIL FILM WHIRL IN HIGHSPEED
TURBO MACHINES0.5*SPEED RADIAL
5. DAMAGED OR WORN GEARS NO: OF TEETH* RPM RADIAL
TABLE 1.1 (a): VIBRATION CAUSES IDENTIFICATION
1.2 APPLICATION OF VIBRATION MONITORING TECHNIQUES
Figure 1.2(b) shows one typical example of the failure rate of components of
different machineries in plants which are maximum for rolling bearings as compared to
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Fig 1.2(a): detection m ethods of failures
vibration
45%
others
4%
acoustic
emission
3%
fluorescence
3%
torque
6%
rotational speed
6%
temperature
10%
oil analysis
23%
vibration
oil analysis
temperature
rotational speed
torque
fluorescence
acoustic emission
others
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other components. One of the reasons why machinery problems are caused by failure of
rolling bearings is that the number of rolling bearings assembled into machinery is a few
orders of magnitude larger than any other machine elements. Among various NDE
techniques, vibration technique is the most commonly used method for the detection of
failure of rolling bearings as shown in figure 1.2 (a)
1.3 CONDITION MONITORING THROUGH VIBRATION
ANALYSIS IN STEEL INDUSTRY
In steel industry, maintenance cost accounts for nearly 10%-15% of the
production cost. Maintenance affects the target, quality and profitability of the plant.
Implementation of modern concepts of condition based maintenance (CBM) can
appreciably reduce the maintenance costs and enhance reliability of machine
performance and quality of the output.
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Fig1.2 (b): failure rate of different machineries of plant
others
24%
rolling bearing
29%
slide way
13%
valve
6%sliding bearing
6% seal
7%
gear
7%
oil pump
8%
valve
sliding bearing
seal
gear
oil pump
slide wa y
rolling bearing
others
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The effectiveness of CBM through vibration analysis can be understood by the
example of the Rourkela Steel Plant (RSP). With implementation of CBM activities at
RSP, there has been substantial growth in all aspects encompassing the maintenance
system Figure 1.3 (a) was responded that the programme for condition monitoring in
RSP has grown from 40 to 140 critical equipments in a span of last three years. There
has been significant increase in the number of major breakdown prevention cases from
10 to 102, which is more than 10 times, during the previous five years, resulting in
substantial financial savings.
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0
2 0
4 0
6 0
8 0
1 0 0
1 2 0
94-95 95-96 96-97 97-98 98-99 99-00
breakdownsprevented
savings
insitu balancing
trend line
N
o
:
o
f
m
a c
h i
n
e
s
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FIG 1.3(A): CONDITION MONITORING IN R S P
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2. ACOUSTIC EMISSION TECHNIQUE
Acoustic emission is the class of phenomenon whereby transient elastic waves
are generated by the rapid release of energy from localized sources within a material.
The energy released travels as spherical wave front and can be picked up from the
surface of a material using highly sensitive transducers, usually electro-mechanical in
nature, placed on the surface of the material.
Figure 2 (a): A E Technique
The wave thus picked up is converted into electrical signal which on suitable
processing and analysis can reveal valuable information about the source causing the
energy release. In metals the different sources are generation and-propagation of cracks,
movement of dislocations, formation and growth of twins, decohesion and fracture of
brittle inclusions, phase transformations etc. In composites, the sources of AE are
matrix cracking, debonding and fracture of fibers.
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2.1 ACOUSTIC EMISSION SET UP
Fig: 2.1(a). TESTING SET UP
The diagnostics can be performed without the product pumping-over
interruption.
Among the existent non-destructive control methods, the acoustic-emission
method is the only one that provides to exclude completely the sudden damage of
constructions, pipelines, and vessels. Originally conceived as an NDT tool for pressure
vessels, Acoustic Emission testing (AE) has become much wider in scope. We now
apply it to all types of process monitoring as well as for its original purposes of flaw
detection and structural integrity inspection. AE sensors respond with amazing
sensitivity to motion in the low ultrasonic frequency range (10kHz - 2000kHz).
Motions as small as 10-12 inches and less can be detected. These sensors can hear the
breaking of a single grain in a metal, a single fiber in a fiber-reinforced composite, and a
tiny gas bubble from a pinhole leak as it arrives at the liquid surface. By detecting
sources as small as these, or as large as brittle crack advance, AE technology warns of
danger, informs about structural health and watches over costly and critical processes.
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2.2. A E DURING HYDRO TESTING OF A HORTON SPHERE
AE monitoring during hydro testing of a 17 m Horton sphere was carried out.
Figure 2.2 (a) shows typical locations of AE sensors (150 kHz resonant frequency each)
mounted on the Horton sphere, along with a typical AE source location map. The hydro
test of the vessel was carried out to a maximum pressure of 22 kg/ cm 2, with periodic
holds at different pressures. A reloading cycle from 20 kg/cm2 to 22 kg/cm2 was
immediately carried out. During the hydro test, AE signals were generated only during
the pressure rise. With increase in pressure, AE signals were generated in newer areas
and the areas where AE occurred in the previous pressure steps do not generate AE inthe subsequent pressure steps. These signals were attributed to local micro-plastic
deformation of the material. A few AE signals were also generated from cracks in
concrete columns that were supporting the vessel. AE monitoring during hydro test was
useful to confirm the integrity of the vessel.
Fig: 2.2(a). A E monitoring during hydro testing of Horton sphere
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3. INFRARED THERMOGRAPHY
Infrared thermography is based on the principle of detection, and measurement
of infrared radiations QR) arising from the natural or stimulated thermal radiation of an
object. All objects around us emit electromagnetic radiations. At ambient temperatures
and above, these are predominantly infrared radiations.
Figure 3 (a): setup for infrared testing of lap joints
3.1 INFRARED TESTING OF LAP JOINTS
This image depicts the setup for infrared testing of lap joints. The images below
are of a such a lap joint with a three poor spot welds in the middle.
Here is the raw thermo graphic data.
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Here is the same data after removing the noise and vertical gradient.
Here is the same data processed for the local gradient in surface temperature.
The above series of images from thermographic data show that sophisticated
post processing of the raw data offers advantages in identifying good spot welds from
poor ones. Processing the matrix data with FFT algorithms and numerical
differentiation brings out important details that are hidden in the raw infrared data. The
strong change in the surface temperature gradients at the two spot welds on the outside
corresponded to high strength welds. The location of the three spot welds in the middle
can be determined and the weak temperature gradients correspond to low strength
welds.
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4. FERROGRAPHY
Ferrography is a state-of-the-art predictive maintenance technique based on wear
debris analysis. It provides a comprehensive non-intrusive evaluation of the health of
lubricated components while the equipment is in running condition. In today’s modern
power generation, manufacturing, refining, transportation, mining and military
operations, the cost of equipment maintenance, service, and lubricants are ever
increasing. Parts, labor, equipment downtime, lubricant prices and disposal costs are a
primary concern in a well run maintenance management program. Machine condition
monitoring based on oil analysis has become a prerequisite in comprehensive
maintenance programs the ferrography laboratory plays a key role in such programs. It
separates and concentrates wear and contaminant particles for microscopic examination.
Particle size, surface characteristics and composition are then used to determine wear
modes inside a machine so that maintenance recommendations can be made.
4.1. WEAR DEBRIS ANALYSIS
The mechanical systems used in plants have interacting surfaces in relative
motion which are lubricated by oil or grease. During operation, there is a steady
generation of wear particles at interacting surfaces caused by load and relative motion.
These wear debris are carried away by lubricant, which give very useful information
regarding the health of the equipment. Over a period of time, various abnormalities,
such as, excessive load, fatigue, corrosion, abrasion, misalignment, lubrication
starvation and capitation, may arise influencing the wear mechanism and formation of
wear debris. The four major findings from ferrography are the mode, rate, severity and
location of wear. A particular wear mechanism typically generates a particular type of
wear debris. The identified wear modes include abrasion, impact, fatigue, erosion,
corrosion, scuffing and severe sliding. The concentration of wear debris indicates the
rate of wear and the size of debris indicates the severity of wear. The color of the
particles identifies the type of material which pinpoints to the affected component.
Thus, an accurate analysis of all these features of 'the wear debris provides a powerful
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means of knowing the actual wear mechanism based on which, suitable corrective
measures can be taken well in advance.
METAL WEAR POSSIBLE ORIGIN.
ALUMINIUM BEARINGS, BLOCKS, BLOWERS, BUSHINGS,
CLUTCHES, PISTONS.
CHROMIUM BEARINGS, PUMPS, RINGS, RODS.
COPPER BEARINGS, BUSHINGS, CLUTHES, WASHERS.
IRON BLOCKS, CRANK SHAFTS, CYLINDERS,DISCS.
SILVER SOLDERS.
TIN PISTONS.
Table 4.1.(a) wear metal origin table
4.2. ANALYSIS OF OIL SAMPLES
Spectrometric analysis is the most commonly used method for trending
concentrations of wear metals. Spectrometric analysis determines the elemental
concentration of various wear metals, contaminants, and additives present in an used oil
sample. But spectroscopy is less sensitive to the larger particles. A spectrometer is an
instrument with which one can measure the quantities and types of metallic elements in
a sample of oil. The operating principle is as follows. A diluted oil sample is pulverized
by an inert gas to form an aerosol, which is magnetically induced to form a plasma at a
temperature of about 9000°C. As a result of this high temperature the metal ions take on
energy, and release new energy in the form of photons. In this way, a spectrum with
different wavelengths is created for each metallic element. The intensities of the
emissions are measurable for each such element by virtue of its very specific
wavelength, calculated in number of ppm (parts per million). A special spectrometer can
detect the very small metal particles in suspension in the oil, i.e. with a size between 0
and 3 microns. Those small particles are a good indication of general wear. The human
eye can detect particles of a size starting from 50 microns, which allows them to be
visualized using more conventional means. Complementary analysis of such larger
particles can be done by spectrometry, by ferrography or by optical or electronic
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- Reduce or eliminate scaffolding costs
- Eliminate costs
- Eliminate unnecessary pipe replacement
- Widely expand possibilities for monitoring
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Fig 5.1(b). Field signature mapping with
Ideal field pattern and
Corrosion distorted field pattern.
Fig 5.1(c). Sensing pins
(electrodes) are distributed in an
array over the monitored area to
detect changes in the electrical field
pattern. The voltage measurements
(the signature).
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Fig 5.1 (d). FIELD PATTERN
The field proven FSM technique detects metal loss due to corrosion by detecting
small changes in the way an induced current flows through a metallic structure. The
system presents graphical plots indicating the severity and location of corrosion, and
calculates actual corrosion and metal loss. Both sensitivity and accuracy are typically
better than 0.5% of remaining wall thickness, but may vary with the application.
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6. CONCLUSION
The implementation of condition monitoring methodologies to components and
plants is very essential for ensuring safety and reliability and for increasing productivity
of plants. Nondestructive evaluation techniques which aim at detection and
characterization of defects, fatigue, stresses, corrosion, dimensional changes and micro
structural degradations in materials, bear unique potential for applications related to the
condition monitoring of components and plants.
It is probably safe to say that most organizations with a significant capital
investment in plant equipment are, these days, employing some form of Condition
Monitoring technology in order to predict at least some failures. This is the time from
which an incipient failure can first be detected, until functional failure occurs. The
primary determinant of frequency of a Condition Monitoring task is the lead time to
failure, or PF Interval. For example, the time interval from when overall bearing
vibration levels reach an "alarm" limit, until the bearing seizes completely. In order to
be completely sure that the failure is detected prior to the functional failure occurring,
the bearing must be monitored at a frequency less than the PF Interval. So far so good-
in theory. Unfortunately, the practice is that the PF Intervals for sophisticated Condition
Monitoring techniques are highly variable. For example, for Vibration Analysis on a
bearing, the PF Interval will vary depending on the type of failure detected, the type of bearing installed, the severity of its operating cycle, the type of lubrication applied,
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ambient temperature conditions and many other factors. To date, no Condition
Monitoring organization can give anything but the most approximate estimate of the PF
Interval. Any error tends to be on the conservative (i.e. too frequent) side.
6.1 SUMMARY OF APPLICABILITY AND CAPABILITY OF
VARIOUS NDT TECHNIQUES
NDT
TECHNIQUE
DETECTION
CAPABILITY
NON CONTACT
INSPECTION
AUTOMATED
INSPECTION
DEFECT
SIZING
VIBRATION VOLUMETRIC POSSIBLE POSSIBLE POSSIBLE
ACOUSTIC
EMISSION VOLUMETRIC POSSIBLE POSSIBLE
NOT
POSSIBLE
I R THERMO-
GRAPHY
SURFACE ,
NEAR
SURFACE
POSSIBLE POSSIBLE POSSIBLE
FERROGRAPHY VOLUMETRIC POSSIBLE POSSIBLE POSSIBLE
F S M
SURFACE,
NEAR
SURFACE
POSSIBLE POSSIBLE POSSIBLE
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7. REFERENCES
1. Dr. C K Mukhopadhayay, Dr. T Jayakumar, Dr. Baldev Raj, ‘Non-Destructive
Evaluation Techniques for Condition Monitoring of Components and Plants’ .
Institute of Engineers (India) Journal, vol.15 , 2005, PP 144-155.
2. B C Nakra & K K Choudhry, ‘Instrumentation Measurement and Analysis’, Tata
Mc Graw Hill, 14th reprint, ISBN : 0-07-451791-0, pp 350-366
3. Sushil Kumar Srivastava, ‘Industrial maintenance management’, S.Chand &
company Ltd, 2002 Reprint, ISBN : 81-219-1663-1, pp 62-106,202-213.
4. Dr. Baldev Raj, NDT for realising better Quality of Life in Emerging Economies
like India, www.ndt.net/article/wcndt00.
5. http://www.engr.du.edu/profile/Marvin.htm
6. http://www.applied-infrared.com.au/thermography
7. http://lubricants.s5.com/index.htm\
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