Smart Sensors.

SMART SENSORS
by
Mr. G. Sattibabu
Assistant Professor
Department of Electronics and Communication Engineering
Aditya College of Engineering & Technology
Aditya College of Engineering & Technology
UNIT - I

Smart Sensor (JNTUK R19 syllabus)
UNIT I: Introduction to Measurement: Measurement units, applications,
elements, choosing appropriate measuring instruments. Instrument Types and
Performance Characteristics: Review of instrument types, Static characteristics,
dynamic characteristics
Error during measurement process: Sources of systematic error, reduction and
quantification of systematic errors, random errors, aggregation of measurement
system errors.
Calibration: Calibration of measuring instruments, Primary calibration, secondary
calibration and field calibration. Calibration methods for different parameters
(temperature, pressure, humidity, flow...etc.). Automatic Calibration mechanism

Introduction to Measurement:
• Measurement techniques have been of immense importance ever since the start of human
civilization, when measurements were first needed to regulate the transfer of goods in barter trade
to ensure that exchanges were fair.
• The massive growth in the application of computers to industrial process control and monitoring
tasks has spawned a parallel growth in the requirement for instruments to measure, record and
control process variables
• As modern production techniques dictate working to tighter and tighter accuracy limits, and as
economic forces limiting production costs become more severe, so the requirement for instruments
to be both accurate and cheap becomes ever harder to satisfy.
This latter problem is at the focal point of the research and development efforts of all instrument
manufacturers

Introduction
to
Measurement:
Universally
accepted
definition

Present-day applications of measuring instruments can be classified into three
major areas.
1) The first of applications of measuring instruments is their use in regulating trade, applying
instruments that measure physical quantities such as length, volume and mass in terms of
standard units.
2) The second application area of measuring instruments is in monitoring functions. These provide
information that enables human beings to take some prescribed action accordingly.
For examples:
 The gardener uses a thermometer to determine whether he should turn the heat on in his
greenhouse or open the windows if it is too hot.
 Regular study of a barometer allows us to decide whether we should take our umbrellas if we
are planning to go out for a few hours.
 There are thus many uses of instrumentation in our normal domestic lives,
 The majority of monitoring functions exist to provide the information necessary to allow a
human being to control some industrial operation or process.
 In a chemical process for instance, the progress of chemical reactions is indicated by the
measurement of temperatures and pressures at various points, and such measurements allow
the operator to take correct decisions regarding the electrical supply to heaters, cooling water
flows, valve positions etc.

3) One other important use of monitoring instruments is in calibrating the instruments used in the
automatic process control systems described below.
The characteristics of the measuring instruments used in any feedback control system are of
fundamental importance to the quality of control achieved.
Thumb Rule: The accuracy and resolution with which an output variable of a process is controlled
can never be better than the accuracy and resolution of the measuring instruments used

Elements of a measurement system
• A measuring system exists to provide information about the physical value of some
variable being measured. In simple cases, the system can consist of only a single unit that
gives an output reading or signal according to the magnitude of the unknown variable
applied to it. However, in more complex measurement situations, a measuring system
consists of several separate elements as shown in Figure 1.2.

1. Primary sensor: this gives an output that is a function of the measurand (the input applied to it). Some
examples of primary sensors are a liquid-in-glass thermometer, a thermocouple and a strain gauge.
2. Variable conversion elements: are needed where the output variable of a primary transducer is in an
inconvenient form and has to be converted to a more convenient form. In some cases, the primary sensor and
variable conversion element are combined, and the combination is known as a transducer.
3. Signal processing elements: exist to improve the quality of the output of a measurement system in some way.
A very common type of signal processing element is the electronic amplifier, which amplifies the output of the
primary transducer or variable conversion element, thus improving the sensitivity and resolution of
measurement.
4. Signal transmission: is needed when the observation or application point of the output of a measurement
system is some distance away from the site of the primary transducer. Sometimes, this separation is made
solely for purposes of convenience, but more often it follows from the physical inaccessibility or
environmental unsuitability of the site of the primary transducer for mounting the signal presentation/recording
unit.
5. signal presentation unit or of a signal-recording unit: The final optional element in a measurement system is
the point where the measured signal is utilized and displayed at the output.

Choosing appropriate measuring instruments
The starting point in choosing the most suitable instrument to use for measurement of a
particular quantity in a manufacturing plant or other system is the specification of the
instrument characteristics required, especially parameters like
 the desired measurement accuracy,
 resolution,
 sensitivity
 dynamic performance
 cost and suitability for the environmental conditions
 ruggedness and durability
 maintenance requirements

Instrument types
1) Active and passive instruments
2) Null-type and deflection-type instruments
3) Analog and digital instruments
4) Indicating instruments and instruments with a signal output
5) Smart and non-smart instruments

Instrument types:
Active and passive instruments
Active instruments are instruments in which the
quantity being measured simply modulates the
magnitude of some external power source.
e.g.; Petrol-tank level indicator in the Fig 1.3.
 the change in petrol level moves a potentiometer
arm, and the output signal consists of a proportion
of the external voltage source applied across the
two ends of the potentiometer.
 The energy in the output signal comes from the
external power source:
 the primary transducer float system is merely
modulating the value of the voltage from this
external power source.
 the external power source is usually in electrical
form, but pneumatic or hydraulic also.
Fig 1.3 Petrol-tank level indicator

Instrument types:
Active and passive instruments
 Passive instruments are instruments in
which output is entirely produced by the
quantity being measured, e.g.; pressure
gauge in the Fig 1.4
 there are no other energy inputs to the
system.
Fig 1.4: Passive pressure gauge.

Instrument types:
Important differences between Active and passive instruments
 One very important difference between active and passive instruments is the level of
measurement resolution that can be obtained. As it is possible to increase
measurement resolution of passive pressure gauge by making the pointer longer, the
scope for such improvement is clearly restricted by the practical limit of how long the
pointer can conveniently be.
 In an active instrument, however, adjustment of the magnitude of the external
energy input allows much greater control over
 In terms of cost, passive instruments are normally of a simpler construction than
active ones and are therefore cheaper to manufacture

Instrument types
Null-type and deflection-type instruments
• Deflection type instruments: The pressure gauge just
mentioned is a good example of a deflection type of
instrument, where the value of the quantity being measured
is displayed in terms of the amount of movement of a
pointer.
• Null-type instruments: An alternative type of pressure gauge
is the deadweight gauge shown in Figure 1.5, which is a null-
type instrument. Here, weights are put on top of the piston
until the downward force balances the fluid pressure.
Weights are added until the piston reaches a datum level,
known as the null point. Pressure measurement is made in
terms of the value of the weights needed to reach this null
position
Figure 1.5 Deadweight pressure gauge.

Instrument types
Analog and digital instruments
An analogue instrument gives an output that varies
continuously as the quantity being measured changes.
The output can have an infinite number of values within
the range that the instrument is designed to measure.
The deflection-type of pressure gauge described earlier
in this chapter (Figure 1.4) is a good example of an
analogue instrument.
 As the input value changes, the pointer moves with a
smooth continuous motion. As the pointer can
therefore be in an infinite number of positions within
its range of movement, the number of different
positions that the eye can discriminate between is
strictly limited.
Fig 1.4: Passive pressure gauge.

Instrument types
Analog and digital instruments
A digital instrument has an output that varies in discrete steps and so can only have a finite number of
values. The rev counter sketched in Figure 1.6 is an example of a digital instrument. A cam is attached to
the revolving body whose motion is being measured, and on each revolution the cam opens and closes a
switch. The switching operations are counted by an electronic counter. This system can only count whole
revolutions and cannot discriminate any motion that is less than a full revolution.
 An instrument whose output is in digital form is therefore particularly advantageous in applications,
as it can be interfaced directly to the digital computer system.
Figure 1.6 Rev counter.

Instrument types
Indicating instruments and instruments with a signal output
Indicating instruments give an audio or visual indication of the magnitude of the
physical quantity measured
The class of indicating instruments normally includes all null-type instruments and
most passive ones. Indicators can also be further divided into those that have an
analogue output and those that have a digital display. A common analogue indicator
is the liquid-in-glass thermometer.
Instruments with a signal output give an output in the form of a measurement
signal whose magnitude is proportional to the measured quantity.

Instrument types
Smart and non-smart instruments
Smart Instrument: An instrument with a microprocessor to do some operations
during and after measurements
 Smart instruments have diagnostics that can detect faults in the installation or
problems with the application, each of which could compromise measurement
quality and/or reliability.
 One of the keys to unlocking the information produced by a smart instrument is
the operator interface. This interface can be the instrument’s local display, a local
handheld HMI (human machine interface), or a networked HMI.
 Information can more readily flow between a technician or an engineer and the
instrument with an HMI as opposed to a local display
Non-Smart Instrument : An instrument that do not have microprocessor

Static characteristics of instruments:
1. Accuracy and inaccuracy (measurement uncertainty)
2. Precision/repeatability/reproducibility
3. Tolerance
4. Range or span
5. Linearity
6. Sensitivity of measurement
7. Threshold
8. Resolution
9. Sensitivity to disturbance
10. Hysteresis effects
11. Dead space
 Valid only in
prescribed
conditions

Dynamic characteristics of instruments:
• Zero order instrument
• First order instrument
• Second order instrument
Valid beyond
the prescribed
conditions

1. Accuracy and inaccuracy (measurement uncertainty)
Accuracy and inaccuracy (measurement uncertainty): The accuracy of an
instrument is a measure of how close the output reading of the instrument
is to the correct value.
• In practice, it is more usual to quote the inaccuracy figure rather than the
accuracy figure for an instrument.
Inaccuracy is the extent to which a reading might be wrong, and is often
quoted as a percentage of the full-scale (f.s.) reading of an instrument.
• For example, a pressure gauge of range 0–10 bar has a quoted inaccuracy
of ± 1.0 % f.s. (±1% of full-scale reading), then the maximum error to be
expected in any reading is 0.1 bar

• Precision is a term that describes an instrument’s degree of freedom from random errors. If a large
number of readings are taken of the same quantity by a high precision instrument, then the spread of
readings will be very small. Precision is often, though incorrectly, confused with accuracy. High
precision does not imply anything about measurement accuracy. A high precision instrument may have
a low accuracy.
• Repeatability describes the closeness of output readings when the same input is applied repetitively
over a short period of time, with the same measurement conditions, same instrument and observer,
same location and same conditions of use maintained throughout.
• Reproducibility describes the closeness of output readings for the same input when there are changes
in the method of measurement, observer, measuring instrument, location, conditions of use and time
of measurement.
NOTE:
spread is referred to as repeatability if the measurement conditions are constant
and as reproducibility if the measurement conditions vary

(a) Low precision, low accuracy (b) High precision, low accuracy (c) High precision, high accuracy

3. Tolerance: Tolerance is a term that is closely related to accuracy and defines the maximum error
that is to be expected in some value.
 When used correctly, tolerance describes the maximum deviation of a manufactured component
from some specified value. e.g. electric circuit components such as resistors have tolerances of
perhaps 5%.
4. Range or Span: The range or span of an instrument defines the minimum and maximum values of
a quantity that the instrument is designed to measure.
5. Linearity: It is desirable that the output
reading of an instrument is linearly
proportional to the quantity being
measured. The non-linearity is then
defined as the maximum deviation of any
of the output readings marked X from this
straight line as shown in Fig 1.8

6. Sensitivity of measurement: The sensitivity of
measurement is a measure of the change in
instrument output that occurs when the quantity
being measured changes by a given amount.
Thus, sensitivity is the ratio of scale deflection
to the value of measurand producing deflection
The sensitivity of measurement is therefore
the slope of the straight line drawn on Figure
1.8.
If, for example, a pressure of 2 bar produces a
deflection of 10 degrees in a pressure
transducer, the sensitivity of the instrument is
5 degrees/bar (assuming that the deflection is
zero with zero pressure applied).

7. Threshold: 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
output reading is of a large enough magnitude to be detectable. This minimum level
of input is known as the threshold of the instrument.
 E.g., if the vehicle starts from rest and accelerates, no output reading is observed
on the speedometer until the speed reaches 15 km/h.
8. Resolution: Resolution is a lower limit on the magnitude of the change in the input
measured quantity that produces an observable change in the instrument output.
Like threshold, resolution is sometimes specified as an absolute value and sometimes
as a percentage of f.s. deflection.

9. Sensitivity to disturbance: All calibrations and specifications of an instrument are only
valid under controlled conditions of temperature, pressure etc. These standard ambient
conditions are usually defined in the instrument specification. As variations occur in the
ambient temperature etc., certain static instrument characteristics change, and the
sensitivity to disturbance is a measure of the magnitude of this change.
Such environmental changes affect instruments in two main ways, known as:
1. Zero Drift
2. Sensitivity Drift

9. Sensitivity to disturbance:
1.) Zero Drift: Zero drift or bias describes the effect where the zero reading of an instrument is
modified by a change in ambient conditions. This causes a constant error that exists over the full range
of measurement of the instrument.
 Quantified by zero drift coefficient
1.) Sensitivity Drift: Sensitivity drift (also known as scale factor drift) defines the amount by which an
instrument’s sensitivity of measurement varies as ambient conditions change. Sensitivity drift is
measured in units of the form (angular degree/bar)/°C
 Quantified by sensitivity drift coefficients
Effects of disturbance Shown in Fig. 1.9

9. Sensitivity to disturbance:
Fig. 1.9 Effects of disturbance:
(a) zero drift;
(b) sensitivity drift;
(c) zero drift plus sensitivity
drift.

10. Hysteresis effects: The non-coincidence
between these loading and unloading
curves is known as hysteresis.
• Maximum input hysteresis and
maximum output hysteresis, as shown in
Figure 1.10. are normally expressed as a
percentage of the full-scale input or
output reading respectively.
• Hysteresis can also occur in instruments
that contain electrical windings formed
round an iron core, due to magnetic
hysteresis in the iron. This occurs in
devices like the variable inductance
displacement transducer Fig. 1.10 Instrument characteristic with hysteresis

11. Dead space: Dead space is
defined as the range of different
input values over which there is
no change in output value.
 Any instrument that exhibits
hysteresis also displays dead
space
Some instruments that do not
suffer from any significant
hysteresis can still exhibit a
dead space in their output
characteristics. Shown in Fig
1.11
Fig. 1.11 Instrument characteristic with dead space

The dynamic characteristics of a measuring instrument describe its behaviour between the
time a measured quantity changes value and the time when the instrument output attains a
steady value in response.
 As with static characteristics, any values for dynamic characteristics quoted in instrument
data sheets only apply when the instrument is used under specified environmental
conditions.
 Outside these calibration conditions, some variation in the dynamic parameters can be
expected.

 In any linear, time-invariant measuring system, the following general relation can be written between
input and output for time (t) > 0:
 where qi is the measured quantity, q0 is the output reading and a0 . . . an, b0 . . . bm are
constants.
 If we limit consideration to changes in the measured quantity only, then above equation reduces to:

1. Zero order instrument
 where K is a constant known as the instrument sensitivity as
defined earlier. Any instrument that behaves according to
equation (1.3) is said to be of zero order type.
 Following a step change in the measured quantity at time t, the
instrument output moves immediately to a new value at the same
time instant t, as shown in Figure 1.12.
 A potentiometer, which measures motion, is a good example of
such an instrument, where the output voltage changes
instantaneously as the slider is displaced along the potentiometer
track.
Fig. 1.12 Zero order instrument
characteristic.

2. First order instrument:

3. Second order instrument:

Error during measurement process:
Errors in measurement systems can be divided into two:
1. Those that arise during the measurement process
2. and those that arise due to later corruption of the measurement signal by induced noise
during transfer of the signal from the point of measurement to some other point
Here we discuss only former i.e.; Errors that arise during the measurement process
Errors arising during the measurement process can be divided into two groups, known
as:
 systematic errors
 random errors.

Systematic errors
Systematic errors describe errors in the output readings of a measurement system that are
consistently on one side of the correct reading, i.e, either all the errors are positive or they
are all negative.
Sources of systematic errors are:
Major sources:
 system disturbance during measurement
 and the effect of environmental changes
(modifying inputs),
 wear in the instrument components
 connecting leads
Some other Sources:
 bent meter needles,
 the use of uncalibrated instruments,
 drift in instrument characteristics
 and poor cabling practices.

Sources of systematic errors are: Major sources
1. System disturbance due to measurement:
Disturbance of the measured system by the act of measurement is a common source of systematic
error.
For example:
• If we were to start with a beaker of hot water and wished to measure its temperature with a
mercury-in-glass thermometer, then we would take the thermometer, which would initially be at
room temperature, and plunge it into the water. In so doing, we would be introducing a relatively
cold mass (the thermometer into the hot water and a heat transfer would take place between the
water and the thermometer. This heat transfer would lower the temperature of the water. Whilst the
reduction in temperature in this case would be so small as to be undetectable by the limited
measurement resolution of such a thermometer,
• The effect is finite and clearly establishes the principle that, in nearly all measurement situations, the
process of measurement disturbs the system and alters the values of the physical quantities being
measured.
• Thus, as a general rule, the process of measurement always disturbs the system being measured.

CASE STUDY: Measurements in electric circuits
 In analysing system disturbance during measurements in electric circuits, Thevenin’s theorem is
often of great assistance.
 For instance, consider the circuit
shown in Figure 1.15 (a) in which
the voltage across resistor R5 is to
be measured by a voltmeter with
resistance Rm. Here, Rm acts as a
shunt resistance across R5,
decreasing the resistance between
points AB and so disturbing the
circuit. Therefore, the voltage Em
measured by the meter is not the
value of the voltage E0 that existed
prior to measurement.
Figure 1.15 (a) (a) a circuit in which the voltage across R5 is to be
measured;

 The extent of the disturbance can be assessed by
calculating the open circuit voltage E0 and
comparing it with Em.
 Thevenin’s theorem allows the circuit of Figure
1.15(a) comprising two voltage sources and five
resistors to be replaced by an equivalent circuit
containing a single resistance and one voltage
source, as shown in Figure 1.15 (b).
 For the purpose of defining the equivalent single
resistance of a circuit by Thevenin’s theorem, all
voltage sources are represented just by their
internal resistance, which can be approximated to
zero, as shown in Figure 1.15 (c).
Figure 1.15 (b) equivalent circuit by Thevenin’s
theorem;
Figure 1.15 (c) the circuit used to find
the equivalent single resistance RAB.

 Analysis proceeds by calculating the equivalent resistances of sections of the circuit and building these up
until the required equivalent resistance of the whole of the circuit is obtained. Starting at C and D, the circuit
to the left of C and D consists of a series pair of resistances (R1 and R2) in parallel with R3, and the equivalent
resistance can be written as
 Moving now to A and B, the circuit to the left consists of a pair of series resistances (RCD and R4) in parallel
with R5. The equivalent circuit resistance RAB can thus be

NOTE: It is thus obvious
that as Rm gets larger, the
ratio Em/E0 gets closer to
unity,
 showing that the
design strategy should
be to make Rm as high
as possible to
minimize disturbance
of the measured
system.

2. Errors due to environmental inputs:
An environmental input is defined as an apparently real input to a measurement system that is actually
caused by a change in the environmental conditions surrounding the measurement system. The fact
that the static and dynamic characteristics specified for measuring instruments are only valid for
particular environmental conditions (e.g. of temperature and pressure), away from the specified
conditions, the characteristics of measuring instruments vary to some extent and cause measurement
errors due to environment input.
The magnitude of this environment-induced variation is quantified by the two constants:
1. Sensitivity drift
2. Zero drift
3. Wear in instrument components:
Systematic errors can frequently develop over a period of time because of wear in instrument
components.
 Recalibration often provides a full solution to this problem.
4. Connecting leads

Reduction of systematic errors
1) Careful instrument design: Careful instrument design is the most useful weapon in the
battle against environmental inputs, by reducing the sensitivity of an instrument to
environmental inputs to as low level as possible.
2) Method of opposing inputs: The method of opposing inputs compensates for the effect
of an environmental input in a measurement system by introducing an equal and
opposite environmental input that cancels it out.
3) High-gain feedback
4) Calibration
5) Manual correction of output reading
6) Intelligent instruments: Intelligent instruments contain extra sensors that measure the
value of environmental inputs and automatically compensate the value of the output
reading.

Random errors
Random errors: Random errors in measurements are caused by unpredictable variations in the
measurement system. They are usually observed as small perturbations of the measurement either side
of the correct value, i.e. positive errors and negative errors occur in approximately equal numbers for a
series of measurements made of the same constant quantity.
 random errors can largely be eliminated by calculating the average of a number of repeated
measurements, provided that the measured quantity remains constant during the process of taking the
repeated measurements.
 The degree of confidence in the calculated mean/median values can be quantified by calculating the
standard deviation or variance of the data,

Random errors
Discussion on mean and median:
 Suppose that the length of a steel bar is measured by a number of different observers and the following set of
11 measurements are recorded (units mm). We will call this measurement set A. 398 420 394 416 404 408
400 420 396 413 430; mean = 409.0 and median = 408
 Suppose now that the measurements are taken again using a better measuring rule, and with the observers
taking more care, to produce the following measurement set B: 409 406 402 407 405 404 407 404 407 407
408; mean = 406.0 and median = 407
 Which of the two measurement sets A and B, and the corresponding mean and median values, should we have
most confidence in? Intuitively, we can regard measurement set B as being more reliable since the
measurements are much closer together. In set A, the spread between the smallest (396) and largest (430)
value is 34, whilst in set B, the spread is only 6.
 Thus, the smaller the spread of the measurements, the more confidence we have in the mean or median value
calculated

Random errors
Discussion on mean and median:
Let us now see what happens if we increase the number of measurements by extending measurement
set B to 23 measurements. We will call this measurement set C. 409 406 402 407 405 404 407 404 407
407 408 406 410 406 405 408 406 409 406 405 409 406 407; Now, mean = 406.5 and median = 406.
 This confirms our earlier statement that the median value tends towards the mean value as the
number of measurements increases.
NOTE: Expressing the spread of measurements simply as the range between the largest and smallest
value is not in fact a very good way of examining how the measurement values are distributed about
the mean value.

Random errors
Discussion on variance and standard deviation :
A much better way of expressing the distribution is to calculate the Variance or Standard
deviation of the measurements.
The starting point for calculating these parameters is to calculate the deviation (error) di of each
measurement xi from the mean value xmean

Problem 3: Calculate 𝜎 and V for measurement sets A, B and C above.

Aggregation of measurement system errors
Errors in measurement systems often arise from two or more different sources, and these
must be aggregated in the correct way in order to obtain a prediction of the total likely
error in output readings from the measurement system.
Two different forms of aggregation are required.
1) Firstly, a single measurement component may have Combined effect of systematic
and random errors:
2) Secondly, a measurement system may aggregation of errors from separate
measurement system components

1) Combined effect of systematic and random errors:
If a measurement is affected by both systematic and random errors that are quantified as
±x (systematic errors) and ±y (random errors),
 One way of expressing the combined error would be to sum the two separate
components of error, i.e. to say that the total possible error is e = ± (x + y).
 However, a more usual course of action is to express the likely maximum error as
follows:

2) Aggregation of errors from separate measurement system components
 A measurement system often consists of several separate components, each of which
is subject to errors.
 Therefore, what remains to be investigated is how the errors associated with each
measurement system component combine together, so that a total error calculation
can be made for the complete measurement system.
 All four mathematical operations of addition, subtraction, multiplication and division
may be performed on measurements derived from different instruments/transducers
in a measurement system.

 If the two outputs y and z of separate measurement system components are to be added
together, we can write the sum as S = y + z. If the maximum errors in y and z are ±ay and
±bz respectively, we can express the maximum and minimum possible values of S as:
 an alternative form such that the most probable maximum error in S is represented by a
quantity e, where e is calculated in terms of the absolute errors as:
Error in a sum:

CALIBRATION
Calibration of measuring instruments:
The ability of all measuring instruments to measure accurately and reliably is to be
proved, to get meaningful results. For this, the results of measurement are to be
compared with higher standards.
The instruments to be used for measurement should be of known accuracy in order
that the results obtained are meaningful.
In order to identify the errors and rectification of errors, the instruments are
compared with masters or standards. This act of comparison is known as calibration

CALIBRATION
Definition of Calibration:
The process of comparison of a device with unknown accuracy to a device
with a known, accurate standard to eliminate any variation in the device
being checked is called calibration.
 So, calibration of a measuring system means introducing an accurately known sample of
the variable that is to be measured and then adjusting the readout device of the
measuring system until its scale reads the introduced known sample of the variable
accurately, i.e the calibration procedure establishes the correct output scale for the
measuring system.
Traceability: Traceability is the property of the results of a
measurement, not of an instrument or calibration report or laboratory.
Traceability means the result of a measurement can be related to a
reference through a series of calibration reports.

CALIBRATION
Why it is necessary to calibrate measuring instruments?
1) The calibration of any measuring system is very important to get meaningful results.
2) In the case where the sensing system and measuring system are different, then it is
imperative to calibrate the system as an integrated whole in order to take into account the
error producing properties of each component.
3) Calibration is usually carried out by making adjustments such that the readout device
produces zero output for zero-measured input, and similarly, it should display an output
equivalent to the known measured input near the full-scale input value.
4) It is important that any measuring system calibration should be performed under
environmental conditions that are as close as possible to those conditions under which actual
measurements are to be made.
5) It is also important that the reference measured input should be known to an as much
greater degree of accuracy – usually, the calibration standard for the system should be at least
one order of magnitude more accurate than the desired measurement system accuracy.

CALIBRATION
1. Specified environmental conditions are to be maintained so that similar
conditions prevail when the system is calibrated and when the actual
measurements are made.
2. The device to be calibrated is checked for any physical defects.
3. The standard measurement system used for calibration should be at
least ten times more accurate than the desired measurement system
accuracy i.e accuracy ratio of 10:1
Steps or precautions to be observed during calibration of a
measurement system:

CALIBRATION
Calibration procedure:
The procedure for calibrating instruments is of three types based on the standard we follow namely
(a) Primary calibration: As per this procedure, a system is calibrated against a primary standard.
While calibrating flow meters, if the flow is determined through measurement of time and volume or
mass of fluid, then it is termed as primary calibration.
(b) Secondary calibration: As per this procedure, a device that has been calibrated by primary
calibration is used as a secondary standard for further calibration of other devices of lesser accuracy
A turbine type flow meter is used as a secondary standard to calibrate other flow devices.
(c) Field calibration: Refers to a company sending trained staff to a client's facility and performing
calibration on-site rather than the client sending their equipment to a lab.
These mobile technicians will bring the right equipment to help them perform their on-site duties
appropriately.

CALIBRATION
Errors Due to Calibration:
1. Any instrument has to be calibrated before it is put to use. Calibration is a process of
giving a known input to the measurement system and taking necessary actions to see that
the output of the measurement system matches with its input.
2. If the instrument is not calibrated properly, it will show reading with a higher degree of
error. This is called a calibration error.
3. Calibration errors are fixed errors as they have been introduced into the measurement
system because of improper calibration.

CALIBRATION
Advantages of Calibration:
 Calibration fulfils the requirements of traceability to national/ international standards
like ISO 9000, ISO 14000, etc.
 Calibration is proof that the instrument is working.
 Confidence in using the instruments.
 Traceability to national measurement standards.
 Reduced rejections, failure rate thus higher return.
 Improved product and service quality leading to satisfied customers.
 Power saving.
 Cost-saving.
 Safety.

CALIBRATION
Calibration methods for different parameters
1. Pressure Calibration
 Pressure calibration is a key function across multiple industries where measurement equipment
is used to monitor process performance and safety, typically measuring gas and hydraulic
pressure.
 For carrying out pressure calibration, numerous types of pressure balances and calibrators are
used together with high accuracy pressure sensors and pressure gages.
2. Temperature Calibration
 In all processed where temperature readings have a critical role, temperature calibration are
conducted and are carried out in a controlled environment.
 In the process of temperature calibration, thermistors, thermocouples or Platinum resistance
thermometers (PRTs), also called resistance temperature devices (RTDs) are usually used.
 A temperature calibration can only be performed by comparing a known standard, in a stable
temperature environment to the probe being tested.

CALIBRATION
3. Flow Calibration
 A flow meter (or flow sensor) is a test device used to measure linear, nonlinear, mass or volumetric flow rate of a
liquid or a gas. The flow rate refers to the speed at which a process fluid is moving through pipelines, orifices, or
vessels at a given time and control and instrumentation engineers need to measure this value in order to monitor and
regulate the speed and efficiency of industrial flow processes and devices.
 Flow calibration services need to be carried out periodically for these flow meters that check product or feedstock
quality and quantity, fuel/energy quantity or function in a critical process, to ensure that measurements are accurate
allowing operations to proceed in a safe and timely manner.
4. Humidity:
Most calibration laboratory equipment and processes are to some degree sensitive to ambient temperature and
relative humidity. Calibration uncertainties depend on maintaining temperature and relative humidity within certain
tolerances.
The humidity generator selected for the calibration system had sufficient accuracy as the relative humidity standard.
However, its inherent temperature accuracy was inadequate for this application. A separate temperature reference
would need to transmit the temperature readings to the computer through a digital interface.

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