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Chapter 1

Introduction to Sensors andMeasurement

EAS3611 - Measurement & Sensors - Md Amzari bin Md Zhahir 201310-September-2013 1

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Chapter Outcomes

At the end of the chapter the student should beable to:

Define in general terms what is a sensor, Define and understand the terms used to describe

the static performance characteristics of sensors,

Determine some of the performance

characteristics of a sensor based on its datasheet, Categorize sensor applications.


EAS 3611 Measurement and Sensors

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Facts on Sensors

World sensor markets (non-military): US$ 61 billion (Exp2010)

Pressure sensor market: ~ US$ 4 billion (Y 2005)

Automotive sensor market: ~ US$ 6.2 billion (Y 2005)

MEMS devices market: ~ US$ 5.6 billion (Y 2005) Big players of the sensor industry:

Chemical industry (Largest nb of sensors)

Automotive industry (Luxury cars have more than 100

sensors) Military industry (largest research budget)

Medical industry (biosensors)



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The 2010 Best of Sensors Expo Award Winners (1)



Shock Recorder from Diversified Technical Systems Inc.

won a gold award (Data Acquisition Products):Size: 65 by 65 by 18 mm,withstand 2000 g of shock,

samples at up to 20,000 sps/channel,

collects up to 1 GB of data to internal flash memory,

operate for up to 24 months on an internal battery

Vibration Dosimeter from Larson Davis, a divison of

PCB Piezotronics Inc.won a gold award:Measures and records the vibration levels that are entering

the hand when workers use powered hand tools

MEMS Digital Vibration Sensor fromAnalog Devices

Inc.won a silver award:designed for industrial equipment monitoring,

70 g dynamic range across three axes,

72.9 Ksps sample rate,

frequency response from DC to 10 kHz

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Energy harvesting wireless sensor node from MicroStrain Inc.

won a silver award:onboard sensing (triaxial accelerometer, humidity sensor,

temperature sensor, and signal conditioning for Wheatstone-bridge-

based devices)

ability to use multiple different types of energy harvesting to power

the node: piezoelectric, electrodynamic, solar, RF field, and

thermoelectric energy harvesters.

Mechanical Energy Harvester fromArveniwon a bronze award:converts actions such as the push of a button into usable electrical energy,

energy conversion efficiency of 20%35%,

energy harvester is piezoelectric,

implemented in a TV remote control.

Modular Wireless Sensor Networking Platform from Libeliumwon a silver award:transmission range up to 40 km,

operation for up to 3 years without recharging the battery,

802.15.4/ZigBee, 858 MHz, or 900 MHz operation,

Built-in carbon dioxide sensors can be used to detect forest fires,

Integrated liquid level sensors can be used to warn of river flooding.

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2013 Awards Ceremony June 5 at3:30 p.m. Sensors Live Theater

Sensors announced the magazine's 2013 "Best of Sensors Expo" Awards foroutstanding achievement onsite at Sensors Expo & Conference 2013. The

awards were presented by Executive Editor Melanie Martella in

the Sensors Live Theater on the Expo Floor.

2013 Winners:

Engineering Team of the Year Award:Kenneth Foust, Intel

Carlos Puig, Qualcomm

Application Award:

Gold Award: Open Geospatial Consortium

Silver Award: SENSUSSBronze Award: OrthoSensor

Honorable Mention Award: Goodyear Tire & Rubber Co. and NASA-Glenn

Research Center

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Application AwardsThe Gold Application Award goes to The Sensor Web Enablement Initiative from the Open Geospatial Consortium.

This initiative standardizes Web service interfaces and data encodings to create building blocks for a world widesensor web, creating a framework of open standards to allow diverse Web-connected sensors and sensor systems to

be accessed in an interoperable, platform-independent, and uniform way for use in disaster management, remote

sensing, environmental monitoring, public safety, and many other applications. As Randy Frank observed, "This is an

extensive standards effort and it could have a huge impact."

The Open Geospatial Consortium's Sensor Web Enablement Initiative

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Innovation Award Winners

This year we have two Gold Innovation Awards. The

first Gold Award goes to Kionix for its KMX61G

magnetic gyro. This combination accelerometer and

magnetometer provides a lower-power alternative to

a gyroscope for consumer electronics, creating a 9-

axis motion sensing system from a 6-axismagnetometer/accelerometer combined with device

sensor fusion software and calibration algorithms

working together to generate accurate emulated

gyroscope outputs. As Melanie Martella notes, "There

are a number of devices that, because of their

stringent power consumption constraints have beenunable to use gyroscopes because of the power

demands involved with their use. This device, by

providing low-power gyroscope emulation, puts that

functionality within their reach.

The KMX61G from Kionix

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Innovation Award Winners

The SL13A NFC Sensory Tag

IC from ams AG

Our second Gold Innovation Award goes to ams

AG for its SL13A NFC Sensory Tag IC. This single-chip combination NFC/RFID tag is optimized for

single-cell, battery-powered smart labels and

incorporates sensor functionality through a built-in

temperature sensor and an external sensor

interface. Suited for use in applications using thin

and flexible batteries, the chip can also bepowered from the RF field. The NFC capability

means that as long as you have an NFC-enabled

device with the appropriate app you can read the

tag; you don't need an installed RFID

infrastructure, although the tag works with RFID,

too. As Frank said, "It's a good execution thatfulfills the promised trend in asset monitoring." It's

powerful, flexible, and can be used for

autonomous long-term asset tracking and

monitoring for things such as buildings and

transportation along with a number of other uses.

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1.2 Sensor Performance Characteristics



Terms used to describe the performances of a sensor.

Indicates how well the instrument is able to measure theinput.

Distinction between static and dynamic characteristics. Onlythe static characteristics is described here.

Sensor characteristics given in Data Sheets:

Only selected information are displayed (marketingdocument)

Information and terms used are different betweenmanufacturers

Difficulty to make an effective comparison between sensors

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Terms Definition

Transfer Function:Functional relationship between input signal and output signal.

Sensitivity:Ratio between a small change in output signal to a small change ininput signal. For a continuous relationship it is the derivative of theTransfer Function.

The more a sensor is sensitive, the more it is able to detect changes

in the measured quantity.

Also called Scale Factor.

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Dynamic Range:Range of the input that produces a valuable output signal. Outsidethis range the measurement is not acceptable. Also called Full-Scale Input.

Full-Scale Output:Range of the output signal.

Accuracy:Largest expected error between actual and ideal output signals. Canbe indicated as a percentage of the Full-Scale Output(e.g. 2%

FSO), or as X.

Hysteresis:Phenomenon that creates a difference in theoutput curve of a sensor when the directionof the input has been reversed.

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Nonlinearity:Maximum deviation from a linear transfer functionover thespecified dynamic range. The error generated is usuallyexpressed in percentage of full scale. Different methods existto express the nonlinearity:

Bandwidth:Range of input signal frequency that can be detected by thesensor in unit of Hertz.

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Noise:Undesired signal that adds up to the sensor output signal.Usually expressed in terms of Noise Densityin unit ofVolts/Hz, if the sensor output is a voltage.The Noiseis then obtained by Noise Density* (Bandwidth).

Precision:Its the ability of the sensor to reproduce a certain set ofreadings (output) for a given input information.

Resolution:Smallest detectable input fluctuation. Not always indicated asit can be derived from the (noise density)/(sensitivity). Lessnoiseimplies better resolution.

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1.3 Categories of Sensor Application



Monitoring Function

The sensor indicates the condition of the environment. It has nocontrol function.

Thermometers and barometers used for weather information, Water, and electric meters at home, Car speed sensor, Aircraft altimeter.

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Control Function

The sensor is a component of a control system.

Aircraft altitude-hold system (pressure sensor)

SENSOR

Comparison Controller AircraftInput: Desired

Altitude Ho

Output:

Real

Altitude H

Measured altitude

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Experimental Engineering Analysis

The sensor is used to solve engineering problems.

Flow analysis : pressure and temperature measurements

Flutter analysis : vibration measurement Wind tunnel testing : force (lift/drag) measurements

As engineers, there are only two basic ways of solvingengineering problems: theory and experimentation.

Some (usually simple) problems can be adequately solved usingtheory alone. Most problems require judiciously selected blend oftheory and experimentation.

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Features of theoretical methods

1. Often give results that are of general use rather than forrestricted application.

2. Invariably require the application of simplifying

assumptions. Thus, not the actual physical system butrather a simplified mathematical model of the system isstudied. This means the theoretically predicted behavior isalwaysdifferent from the real behavior.

3. In some cases, may lead to complicated mathematical

problems. This has blocked theoretical treatment of manyproblems in the past. Today, increasing availability ofhigh-speed computing machines allows theoreticaltreatment of many problems that could not be so treatedin the past.

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Features of theoretical methods (cont.)

4. Require only pencil, paper, computing machines, etc.Extensive laboratory facilities are not required. (comecomputers are very complex and expensive, but they can

be used for solving all kinds of problems. Much laboratoryequipment, on the other hand, is special-purpose andsuited only to a limited variety of tasks.)

5. No time delay engendered in building models, assemblingand checking instrumentation, and gathering data.

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Features of experimental methods

1. Often give results that apply only to the specific systembeing tests. However, techniques such as dimensionalanalysis may allow some generalization.

2. No simplifying assumptions necessary if tests are run on anactual system. The true behavior of the system us revealed.

3. Accuratemeasurements necessary to give a true picture.This may require expensive and complicated equipment. Thecharacteristics of all the measuring and recording equipmentmust be thoroughly understood.

4. Actual system or a scale model required. If a scale model isused, similarity of all significant features must be preserved.

5. Considerable time required for design, construction, anddebugging of apparatus.

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Types of experimental-analysis problems

1. Testing the validity of theoretical predictions based onsimplifying assumptions; improvement of theory, based onmeasured behavior. Example: frequency-response testing

of mechanical linkage for resonant frequency.2. Formulation of generalized empirical relationships in

situations where no adequate theory exists. Example:determination of friction factor for turbulent pipe flow.

3. Determination of material, component, and system

parameters, variables and performance indices. Example:determination of yield point of a certain alloy steel, speed-torque curves for an electric motor, thermal efficiency of asteam turbines.

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Types of experimental-analysis problems (cont.)

4. Study of phenomena with hopes of developing a theory.Example: electron microscopy of metal fatique cracks.

5. Solution of mathematical equations by means of analogies.

Example: solution of shaft torsion problems bymeasurements on soap bubbles.

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Example: Sensitivity



Consider a thermocouple with the following input/output relationship:V = c0+ c1T + c2T

2

where V, in volt, is the output voltage from the thermocouple andT, in kelvin, the measured temperature. The coefficients c0, c1, and

c2are specific to the thermocouple.

Determine the sensitivity S of this sensor.

S = dV / dT

= c1 + 2c2T

Note that the sensitivity is not

constant in that particular example.But it can be constant for a linearinput/output relationship.

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Example: Accuracy



Consider a thermometer, with an accuracyof 2oC, used tomeasure the room temperature.

At a given time and place the thermometer output is the measuredtemperature Tmeas=23

oC

The true valueof the temperature (or of any other measuredquantity) cant be determined experimentally, as it would require a

perfect sensor.

Thats why the accuracy is so important as it gives us an ideaof where is the true value.

For this example the error realized on the measurement (e=Tmeas Ttrue) is between -2oC and +2oC. Consequently the true

temperature(Ttrue=Tmeas + e) belongs to the interval

[Tmeas -2oC, Tmeas +2

oC] = [21oC, 25oC]

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Example: Accelerometer Data Sheet



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Calculation Slide



Sensitivity: 312 mV/gfor an input acceleration of 1 g, the output isequal to 312mV

If the input acceleration is 2g, the output voltage of the accelerometer is

2x312=624mV

If the voltage reading is =1V, What is the input acceleration?

A=1/.312=3.2g=3.2x9.81ms-2

Dynamic Range:

[-2g;+2g]

Accuracy:

Usually difficult to evaluate a priori

Non linearity:0.2% of Full Scale (FS). =0.2x4g/100=0.008g

Bandwidth:

From 0 Hz to 5000 Hz

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