CHAPTER ONE: Introduction to Instrumentation and Measurement.pptx

Chapter One
Introduction to Measurement &
Instrumentation
AMU-SC | Ashenafi B. 1
Arba Minch University
Sawla Campus
Department of Electromechanical Engineering
Course: Instrumentation Engineering & Measurement
(EMEg4262)
Instructor:
Mr. Tadesse, A.B. (Control & Instrumentation Engineer)

Why do we measure parameters?
• To understand, or reveal insight and predict
variables.
• In the case of industry, to improve quality and
efficiency, and to maintain proper operation.
• Measuring is the process of learning about the
parameters.
• Different scholar quote:
“If you can’t measure it, you can’t improve it.”

Introduction
Measurement and Instrumentation
• Measurement:– the process of determining the quantity
of a variable by means of appropriate measuring
instruments.
• It is a comparison between a standard and what we want
to measure (the measurand).
• A method to obtain information regarding the physical
values of the variables.

Cont’d
• Basic requirements for a meaningful measurement is:
 the standard used for comparison purposes must be accurately defined
and should be commonly accepted.
 the apparatus used and the method adopted must be provable
(verifiable).
• Measurement involve the use of instruments as a physical
means of determining quantities or variables.
• Because of modular nature of the elements within it, it is
common to refer the measuring instrument as a
measurement system.

Instrumentation
• Instrumentation is a collective term for measuring
instruments that are used for measuring,
indicating and recording physical quantities.
• Instrumentation is the design, equipping, and/or
use of measuring instruments in determining real-
life conditions in a plant's process, as for
observation, measurement and control.

Evolution of Instruments
Mechanical
Instrument
Electrical
Instrument
Electronic
Instrument
• Very reliable for static and stable conditions, however
unable to respond rapidly to measurements of dynamic
and transient conditions.
• Indicating the output are rapid than
mechanical methods, however it
depends on the mechanical movement
of the meters.
• It is more reliable than other system.
• It uses semiconductor devices and
weak signal can also be detected.

• An instrument is a device in which we can determine the magnitude or value
of the quantity to be measured.
• The measuring quantity can be voltage, current, power, energy and etc.
• Generally, instruments are classified in to two categories:
Classification of Instruments
Instrument
Absolute
Instrument
Secondary
Instrument

 Absolute/primary instrument determines the magnitude of the quantity to be measured in terms of
the instrument parameter.
 We have to calculate the magnitude of the measuring quantity, analytically which is time consuming,
because each time the value of the measuring quantities varies.
 These types of instruments are suitable for laboratory use.
Example: Tangent galvanometer (for current measurement)
Cont’d
From figure, B=Bh tanθ. This is known as
tangent law of magnetism.

 Secondary instrument: determines the value of the quantity to be measured
directly.
 Generally, these instruments are calibrated by comparing with another standard
secondary instrument.
Examples: voltmeter, ammeter, wattmeter, and etc.
Cont’d

• Indicating Instrument:
This instrument uses a dial and pointer to determine the value of measuring
quantity. The pointer indication gives the magnitude of measuring quantity.
• Recording Instrument:
This type of instruments records the magnitude of the quantity to be
measured continuously over a specified period of time.
• Integrating Instrument:
This type of instrument gives the total amount of the quantity to be
measured over a specified period of time.
Cont’d

Functional Elements of Measuring System
• The main functional elements of a measurement system are:
I. primary sensing element;
II. variable conversion element;
III. variable manipulation element;
IV. data transmission element;
V. data presentation element; and
VI. data storage and playback element
Data Conditioning Element

PRIMARY
SENSING
ELEMENT
VARIABLE
CONVER
-SION ELEMENT
VARIABLE
MANIPULATION
ELEMENT
DATA
TRANSMISSION
ELEMENT
DATA CONDITIONING ELEMENT
INTERMEDIATE STAGE
DETECTOR
TRANSDUCER STAGE
TERMINATING
STAGE
QUANTITY
TO BE
MEASURED
(Measurand)
DATA PRESENTA
TION ELEMENT
Cont’d
DATA STORAGE
AND PLAYBACK
ELEMENT

Primary Sensing Elements:
 The quantity or the variable which is being measured (i.e., CURRENT) makes its first
contact with primary sensing element (i.e., COIL) of measurement.
 PSE receives signal of the physical quantity to be measured as a I/P (input) with help of
detector.
Variable Conversion Element:
 The measured signal is then immediately converted into a suitable form; it may be a
analogous electrical signal, mechanical signal or any other form using transducer.
 For the instrument to perform the desired function, it may be necessary to convert this
output to some other suitable form.
Cont’d

Variable Manipulation Element:
 The function of this element is to manipulate the signal presented to it preserving the
original nature of the signal.
Data Presentation Element:
 The information about the quantity under measurement has to be conveyed to the
personnel handling instrument or the system for monitoring, control, or analysis purposes.
This function is done by data presentation element.
 In case data is to be monitored, visual display devices are needed. These devices may be
analog or digital indicating instruments like ammeters, voltmeters etc.
Cont’d

 In case data is to be recorded, recorders like magnetic tapes, high speed camera &
TV equipment, CRT, printers may be used.
Example: Ammeter
Cont’d

Function of Measurement System
• Functions of instrument and measuring system can be classified into
four major parts. They are:
I. Indicating Function: supplying information concerning the variable quantity
under measurement.
II. Recording Function: the instrument makes a written record, usually on
paper, of the value of the quantity under measurement against time or against
some other variable.
III. Signal Processing: modifying the measured signal to facilitate recording /
control.
IV. Controlling Function: the system to control the original measured variable
or quantity.

Application of Measurement System
• Before discussing the instrument characteristics, construction and
working, it is pertinent to understand the various ways in which the
measuring instruments are put in use.
• Different applications of the instruments and measurement systems
are:
i. Monitoring a process/operation: indication the value/condition of
parameter.
ii. Control a process/operation: corrective action
iii. Experimental engineering analysis: to find out solution of the
engineering problems.

Control a Process
• Measurement of a variable and
its control are closely
associated.
• To control a process variable,
e.g., temperature, pressure or
humidity etc., the prerequisite
is that it is accurately
measured at any given instant
and at the desired location.
Figure: Process control system.

Unit of Measurement & Dimensions
• The standard measure of each kind of physical quantity is called a
unit.
1. CGS system: called Gaussian system of units.
• In this length, mass and time have been chosen as the fundamental
quantities and corresponding fundamental units are centimetre (cm),
gram (g) and second (s) respectively.
2. MKS system: called Giorgi system of unit.
• In this system also length, mass and time have been taken as
fundamental quantities, and the corresponding fundamental units are
metre, kilogram and second.

3. FPS system: In this system foot, pound and second are used
respectively for measurements of length, mass and time.
• In this system force is a derived quantity with unit poundal.
4. SI System: It is known as International system of units, and is
extended system of units applied to whole physics.
• There are seven fundamental quantities in this system.
Cont’d

S.No. Basic Quantity Name Symbol
1 Length Meter M
2 Mass Kilogram Kg
3 Time Second S
4 Electric Current Ampere A
5 Temperature Kelvin k
6 Amount of Substance Mole Mol
7 Luminous Intensity Candela Cd
Cont’d

• Units are sub-divided into 2 categories:
1. Fundamental units
2. Supplementary and Derived units
1. Fundamental units: units for fundamental or base quantities (like
length, mass, time, etc.).
• It was developed and recommended by general conference on weights
and measures in 1971.
Cont’d

Derived Units: Other physical quantities derived from the base quantities can be
expressed as a combination of the base units.
Examples:
Force(f) = Mass x acceleration = m x a = kg ms-2 (newton, N)
Pressure(p) = force/area = (f/a) = kg ms-2/m2 (pascal, pa)
Frequency(f) = 1/period = (1/T) = 1/s = s-1 (hertz, hz)
Cont’d

• Supplementary Units: there are two supplementary units, which are shown in
table below:
• Dimensions: are the representation of physical quantities or derived quantities
in the form of fundamental quantities without its numerical values.
S.No.
Supplementary Fundamental
Quantities
Supplementary
Unit
Symbol
1 Plane angle radian rad
2 Solid angle steradian Sr
Cont’d

CH
Cont’d

Standard
• Mainly used for calibration purpose.
• Standards are used to determine the values of other physical quantities
by comparison method.
1. International Standards
• International standards are defined by the international agreement.
These standards are maintained at the international bureau of weights
and measures and are periodically evaluated and checked by absolute
measurements in terms of fundamental units of physics.
• These international standards are not available to the ordinary users
for the calibration purpose.

Example: International ohms, amperes, etc.
Note: international standard units are replaced in 1948 by absolute units (these units are
more accurate).
1 international ohm = 1.00049 absolute ohm
1 international ampere = 0.99985 absolute ampere
2. Primary Standards
 These primary standards are maintained at national standard laboratories in different
countries.
 These are not available for use, outside the national laboratories.
 The main function of the primary standards is the calibration and verification of
secondary standards.
Cont’d

3. Secondary Standards
 These are used by the measurement and calibration laboratories in industries
and are maintained by the particular industry to which they belong.
 Each industry has its own standards.
4. Working Standards
 These standards are used to check and calibrate laboratory instruments for
accuracy and performance.
Example: manufacturers of electronic components such as Capacitors, Resistors
etc.. use working standards for checking the component values being manufactured.
Cont’d

Calibration
• Calibration of all instruments is important since it affords
the opportunity to check the instruments against a known
standard and subsequently to find errors and accuracy.
• Calibration procedure involve a comparison of the
particular instrument with either
 a Primary standard;
 a secondary standard with a higher accuracy than the instrument
to be calibrated; or
 an instrument of known accuracy.

• Error is the deviation of the true value from the desired value or the difference between the
measured value and the actual value.
 True value: the average value of an infinite number of measured values.
 Measured value: the estimated value of true value.
• Error may be expressed either as absolute error or percentage error
Absolute Error:
E = Yn - Xn
Where, E = Absolute error, Yn=Expected value and Xn=Measured value
Percentage Error / Percentage Relative Error:
Er = {[Yn - Xn] / Yn} x 100
Where, Er = Relative error
Error

Accuracy
• The degree of exactness (closeness) of a measurement compared to the expected
(desired) value. Or how close a measured value is to the actual value
• In most instrument, the accuracy is guaranteed within a certain percentage of full
scale reading.
Note: Percentage error is more frequently expressed as accuracy rather than error.
Therefore,
A = 1 – Er = 1 - {[Yn - Xn] / Yn}

Precision
• A measure of the consistency or repeatability of measurement. (or) it is the
consistency of the instrument output for a given value of input. (or) how close the
measured values are to each other (in each iteration).
Note: The accuracy and precision of an instrument depends upon its design,
material used, and workmanship that goes into making of the instrument.

Cont’d

Types of Errors
a) Gross Error (Human Error)
• These errors are due to human in reading and recording or lack of experience
while taking the measurement values.
• The values of gross errors will vary from observer to observer.
• Sometimes, the gross errors may also occur due to improper selection of the
instrument.
• We can minimize the gross errors by following these two steps.
Choose the best suitable instrument, based on the range of values to be
measured.
 Note down the readings carefully.

b) Systematic Error
• If the instrument produces an error, which is of a constant uniform deviation during its operation is
known as systematic error.
• The systematic errors that occur due to fault in the measuring device (i.e., defective or worn parts
or ageing or environment effect on the instrument), or occur due to the characteristics of the
materials used in the instrument.
Types of Systematic Errors
• The systematic errors can be classified into the following three types.
I. Instrumental Errors: occur due to wrong construction of the measuring instruments
(i.e., shortcomings of the instrument & loading effect).
II. Environmental Errors: occur due to some external conditions mainly change in
environment such that change in pressure, temperature, humidity or due to magnetic
field. These errors are avoided by air-conditioning, sealing certain components, using
magnetic shield, etc.…
Cont’d

III. Observational Errors: occurs due to wrong observations or reading in the
instruments. Parallax errors belong to this type of errors.
• In order to reduce the PARALLAX error highly accurate meters are needed:
meters provided with mirror scales.
c) Random Errors
• Random errors are caused by the sudden change in experimental conditions or
noise or tiredness in the working persons.
• Hence, it is not possible to eliminate or minimize these errors.
Example: sudden changes in humidity, unexpected change in temperature and
fluctuation in voltage.
• These errors may be reduced by taking the average (i.e., statistical analysis) of
a large number of readings.
Cont’d

Performance Characteristics of Instruments
• The performance characteristics of an instrument are mainly divided
in two categories:
1. Static Characteristics: used to measure the quantities which are
slowly varying with time or mostly constant.
2. Dynamic Characteristics: when the quantity under measurement
changes with time, it is necessary to study the dynamic relations
existing between input and output.
• Dynamic relations of parameters are generally expressed with the help
of differential equations.

Static Characteristics
1. Accuracy
2. Precision
3. Sensitivity / Sensitivity Drift
4. Range / span
5. Linearity
6. Threshold
7. Hysteresis
8. Resolution
• The various static characteristics are:

1. Accuracy
• It is concerned on how close a measured value is to the actual value. The accuracy
can be expressed in the following ways.
I. Accuracy as ‘Percentage of Full Scale Reading’
• In case of instrument having uniform scale, the accuracy can be expressed as
percentage of full scale reading.
Example: the accuracy of an instrument having full scale reading of 50 units may
be expressed as ±0.1% of full scale reading. From this accuracy indication,
practically accuracy is expressed in terms of limits of error.

• So for the accuracy limits specified above, there will be ±0.05 units
error in any measurement.
• So for a reading of 50 units, there will be error of ±0.05 units i.e.
±0.1%, while for a reading of 25 units, there will be error of ±0.05
units in the reading i.e. ±0.2%.
II. Accuracy as ‘Percentage of True Value’
• This is the best method of specifying the accuracy.
• It is to be specified in terms of the true value of quantity being
measured.
For example: it can be specified as ±0.1% of true value.
Cont’d

III. Accuracy as ‘Percentage of Scale Span’
• For an instrument, if amax is the maximum point for which scale is
calibrated (i.e., full scale reading) and amin is the lowest reading on
scale; then (amax - amin) is called scale span or span of the instrument.
• Thus, for an instrument having range from 25 units to 225 units, it can
be specified as ±[(0.2/100) x (225-25)] (i.e., ±0.2%.) which is ±0.4 units
error in any instrument.
IV. Point Accuracy
• Such an accuracy is specified at only one particular point of scale.
• It does not give any information about the accuracy at any other point
on the scale.
Cont’d

2. Precision
• It is the measure of the consistency or repeatability of the measurements.
• The precision is composed of two characteristics.
i. Conformity: compliance with standards, or measurement matching with desired value.
ii. Number of significant figures: precision of the measurement is obtained from the number
of significant figures, in which the reading is expressed.
For example: a resistance of 110Ώ, specified by an instrument may be closer to 109Ώ or
110Ώ. Thus, there are 3 significant figures.
• While if it is specified as 110.0Ώ, then is may be closer to 110.1Ώ or 109.9Ώ. Thus, there
are also 3 significant figures.

3. Sensitivity
• The sensitivity denotes the smallest change in the measured variable to which the
instrument responds.
• It denotes as the ratio of the changes in the output to a change in the value of the
quantity to be measured (input).

Cont’d
Example: Sensitivity of a spring balance can be expressed as 25 mm/kg (say), indicating
additional load of 1 kg will cause additional displacement of the spring by 25mm
• Deflection factor (Inverse sensitivity) = 1/Sensitivity

4. Sensitivity Drift
• It deﬁnes the amount by which an instrument’s sensitivity of measurement varies as
ambient conditions change (i.e., due to external conditions).
• In order to avoid such sensitivity drift, sophisticated instruments are either kept at
controlled temperature, or suitable in-built temperature compensation schemes are
provided inside the instrument.
Example:
• Suppose the sensitivity of the spring
balance mentioned above is 25 mm/kg at
20 oC and 27 mm/kg at 30oC.
• Then, the sensitivity drift/oC is 0.2
(mm/kg)/oC.

5. Resolution/Discrimination
• The smallest change in input reading that can be traced accurately, or
It defines the smallest change in measured quantity that causes a
observable change in its output.
For example: In a temperature transducer, if 0.2oC is the smallest
temperature change that observed, then the measurement resolution is
0.2oC.
Note:
• Resolution is the smallest portion of the signal that can be observed, whereas
Sensitivity is the smallest change in the signal that can be detected.

6. Hysteresis
• Hysteresis is basically dependence on the state of a system on its
history.
• It is non-coincidence of loading and unloading whether it is an
electrical or a mechanical system.
• Which means, for an instrument or system, when an input varies from
zero to full scale and then back to zero, its output varies.
• It can occur due to gear backlash in mechanism, magnetic
hysteresis or due to elastic hysteresis.

For example: a magnetic hysteresis is shown below. It is characteristics
of flux density, B and magnetizing force, H.
• There are two outputs in hysteresis for increasing and decreasing the
value of the input.
Cont’d

7. Linearity
• Linearity is the static characteristics of an instrument or measurement system, in
which output is linearly proportional to the input.
• It also defined as the maximum deviation from the linear characteristics as
percentage of the full-scale output.

• If the input to an instrument is gradually increased from zero, the input will have
to reach a certain minimum level before the change in the instrument’s output
reading.
• This minimum value of input below which no output can be appeared is known as
the threshold of the instrument.
Example: Eddy current Speedometer used in automobiles, typically have a
threshold of about 15km/h.
8. Threshold

9. Zero Drift
• It describes the effect where the zero reading of an instrument is modified by a
change in ambient conditions.
• Zero drift is normally removable by calibration.

• Dead space is deﬁned as the range of different input values over
which there is no change in output value.
10. Dead Zone / Dead Space

11. Range
• The input range of an measuring device is specified by the minimum
and maximum values of input variable (Xmin to Xmax).
For example: from -10 to +150 oC (for the measurement device with
temperature input).
• The output range of a measuring device is specified by the minimum
and maximum values of output variable (Ymin to Ymax).

12. Span
• The input span of a measuring devices is specified by the difference
between maximum (Xmax) and minimum (Xmin) values of input
variables: (Xmax - Xmin ).
• In the case of a thermometer, its scale goes from −40°C to 100°C.
Thus, its span is 140°C.

Dynamic Characteristics
• The various dynamic characteristics are:
1. Speed of response
2. Measuring lag
3. Fidelity
4. Dynamic error

• Speed of response: the rapidity with which a measurement system
responds to changes in the measured quantity.
• Measuring lag: retardation delay in the response of a measurement
system to changes in the measured quantity.
It is of 2 types:
I. Retardation type: The response begins immediately after a change in
measured quantity has occurred, but have a slow progress.
II. Time delay: The response of the measurement system begins after a dead
zone after the application of the input.
Cont’d

• Dynamic error:
• Otherwise called as measurement error.
• Difference between the true value of the quantity changing with time and the
value indicated by the measurement system (i.e., provided no static error is
assumed).
• Fidelity: degree to which a measurement system indicates changes in
the measurand quantity without dynamic error.
Cont’d

Statistical Evaluation of Measurement Data
• Out of all the various possible errors, the random errors cannot be determined in
the ordinary process of measurements. However, these errors can be treated
mathematically.
• The mathematical analysis of the various measurements is called statistical
analysis of the data.
• For statistical analysis, the same reading is taken number of times, generally using
different observers, different instruments & by different ways of measurement.
• The statistical analysis helps to determine analytically the uncertainty of the final
test results.
• From statistical analysis tools, some are:
 Arithmetic mean & median
 Average deviation

60
Arithmetic Mean
• The most probable value of measured variable is the arithmetic
mean of the number of readings taken.
• It is given by:
Where, = arithmetic mean
x1, x2, …, x3 = reading of samples
n = number of readings
n
x
n
x
x
x
x n 


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x
AMU-SC | Ashenafi B.

61
Deviation
• Deviation is departure of the observed reading from the arithmetic
mean of the group of readings.
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62
Standard Deviation
• The average amount of variability in the database.
• The standard deviation of an infinite number of data is defined as
the square root of the sum of the individual deviations squared
divided by the number of readings.
 
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Note: ‘n-1’ is a Bessel’s correction to remove biasness from square root, or to
yield unbiased variance.

63
Variance
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• The expectation of the squared deviation of a random variable
from its population mean or sample mean.

64
Probable Error
• Regular deviation within a determined distance on each side of the mean of a
frequency curve.
• It is the value that added or subtracted from the coefficient of correlation (r) to get
the upper & lower limit respectively, within which the value of the correlation
expectedly lies.
• Probable error of one reading (r1),
r1 = 0.6745 * S.D.
• Probable error of mean (rm):
1
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

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65
Problem
Question: The following 10 observation were recorded when
measuring a voltage:
41.7, 42.0, 41.8, 42.0, 42.1, 41.9, 42.0, 41.9, 42.5, 41.8 volts.
1. Mean
2. Standard Deviation
3. Probable Error
4. Range and Span.

66
Answer
• Mean = 41.97 volt
• S.D = 0.22 volt
• Probable error of a single observation (r1) = 0.15 volt
• Probable error of mean (rm) = 0.05
• Range = 41.7 volt to 42.5 volt
• Span = 0.8 volt.

-2
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-2
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Signal
Signal
+
Noise
Noise and Interference

• Noise: can be characterized as any disturbance that tends to obscure
a desired signal. It can be generated within a circuit or picked up from
external nature or artificial sources.
• Interference: is noise that tends to obscure the useful signal. It is
usually caused by electrical sources, but can be induced from other
physical sources such as mechanical vibration, acoustical feedback, or
electrochemical sources.
• The distinction between interference and noise is that interference is
artificial noise (radio frequency jammer) while noise can be natural
(thermal noise) or man made.
Cont’d

Classification/Source of Noise
• Internal Noise
1. Thermal Noise: caused by the random motion of charged particles in the
sensors and amplifiers.
2. Contact Noise: excess noise, flicker noise, or pink noise.
3. Shot Noise: originates from the discrete nature of electric charge (i.e.,
random fluctuation of DC current), or from quantum mechanical events.
• External Noise
1. Conductive Coupling: a power line transmits surge, ripple, and spike noise.
2. Electric and Magnetic Field: capacitive coupled interference & magnetic
field interference.
3. Power Line Interference: caused by an external source that introduces
unwanted voltage in the circuit, called hum in audio system.

Effects of Noise
• Affects operation stability and performance of the system.
• Reduces accuracy and repeatability of measurements.
• Introduces distortion in sound signals.
• Introduces errors in control systems.

• RMS (Root Mean Square) value:
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where T is a suitable averaging time interval. A longer T usually gives a more accurate
rms measurement.
• It indicates the normalized noise power of the signal.
• Signal-to-Noise ratio (SNR) (in dB):
• Noise Summation:
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,
,
2
,
2
,
log
20
log
10
log
10
vn2(t)
vn1(t)
vno(t)=vn1(t)+vn2(t)
=
   
 
   


 


 


 

 

sources
signal
two
the
between
n
correlatio
T
n
n
values
squared
mean
individual
rms
n
rms
n
T
n
n
rms
no
dt
t
v
t
v
T
v
v
dt
t
v
t
v
T
v








0 2
1
2
,
2
2
,
1
0
2
2
1
2
,
2
1
Noise Analysis
71

What to Do?
How can we eliminate or reduce the undesirable effects of noise?
• Grounding/shielding electrical connections;
• Filtering (smoothing);
• Averaging several measurements;
• Keep the connecting wires as short as possible; and
• Keep signal wires away from noise sources.

The End!!!

CHAPTER ONE: Introduction to Instrumentation and Measurement.pptx

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