1. UNIVERSITÁ DEGLI STUDI DI SALERNO
Bachelor Degree in Chemical Engineering
Course: Process Instrumentation and Control (Strumentazione e Controllo dei Processi Chimici)
Measuring devices of the main process variables
General properties of sensors
Rev. 2.3 – February 28, 2019

2. Process Instrumentation and Control - Prof. M. Miccio
SENSORS
EXAMPLES IN EVERYDAY LIFE
Fever thermometer
Kitchen balance
Microphone
EXAMPLES FROM THE PROCESS INDUSTRY:
see also:
§ Stephanopoulos, “Chemical process control: an Introduction to theory and practice”, Prentice Hall, 1984
September 11, 2019
Process Instrumentation and Control - Prof. M. Miccio

3. GENERAL BLOCK DIAGRAM FOR A PROCESS SENSOR
Energy supplier
Acquisition by the control system
Measured system
Signal conditioning system
Primary measuring element
Transducer
Mechanic/pneumatic signal
Electric signal
Measured entity
Real measuring instrument
NOTE:
Sometimes Primary measuring device and the Transducer coincide!
September 11, 2019
Process Instrumentation and Control - Prof. M. Miccio

4. Process Instrumentation and Control - Prof. M. Miccio
SENSORS Definitions
TRANSDUCER:
Device that converts the measure of a physical quantity or a process variable (temperature, pressure, flowrate, etc.) in a electric variable (voltage and current), connected to it. The transducer is called only with the name of the measured variable because the type of output signal is always electric, e.g. pressure transducer.
TRANSMITTER: the word “transmitter” is commonly used for a transducer using a direct current as output signal, normally in the range 4-20 mA. It allows to transmit the signal for long distance (up to few kilometers from the measuring point).
MEASURED ENTITY: physical quantity or process variable that we want to measure with a sensor.
MEASURING RANGE: it is the set of values that the sensor is able to measure. They are between a minimum Xmin and a maximum Xmax
The maximum value is commonly called full scale
The difference (Xmax – Xmin) is commonly called span
September 11, 2019
Process Instrumentation and Control - Prof. M. Miccio

5. GENERAL PROPERTIES OF SENSORS
ACCURACY:
It estimates the closeness of the measure to the true value of the measurement. It defines the maximum deviation between the measure provided by the sensor and the real value.
The accuracy can be expressed as a percentage of the measuring range or of the full scale if the minimum of the measuring rage is zero
Percentage of the measuring range of full scale (dimensionless)
or it can be expressed as a percentage of the measure (that is the true value)
Percentage of the measure (dimensionless):
- ɛa is more constraining
- εf is not useful for wide deviation of the measure
- a small percentage of the full scale error can correspond to a large error if the measured variable is close to the minimum of the measuring range
Bias (Xm – Xv)
The accuracy is sometimes expressed as an absolute value: e.g.: for a temperature sensor, accuracy± 1oC of a measuring range 200400oC
September 11, 2019
Process Instrumentation and Control - Prof. M. Miccio

6. GENERAL PROPERTIES OF SENSORS
REPEATABILITY:
It is the ability to provide a measured value Xm with a deviation as small as possible with respect to a true value Xv that remains constant.
Precision is synonymous with repeatability.
It is calculated as standard deviation.
CALIBRATION:
Procedure or method of adjusting parameters or "settings" (positioning) of the sensor, which has the purpose of bringing together and possibly making Xm coincide with Xv , this latter referring to another sensor of known and great accuracy.
RANGEABILITY (or TURN-DOWN):
It is the ratio between the full scale value and the infimum of the measuring range at which constant values of accuracy and repeatability are considered (e.g.: 20:1).
In trade, it is the ratio between the supremum and the infimum of the measuring range.
September 11, 2019
Process Instrumentation and Control - Prof. M. Miccio

7. ACCURACY vs. REPEATABILITY
Measured variable
repeatable and inaccurate measure
TRUE VALUE
UNrepeatable and accurate measure
TIME
from Magnani, Ferretti e Rocco (2007)
September 11, 2019
Process Instrumentation and Control - Prof. M. Miccio

8. GENERAL PROPERTIES OF SENSORS
STATIC CHARACTERISTIC
It is represented by diagram or analytic form the “static” relation (all the variables are constant with time) between the measured variables and the output signal of the measuring element (or the transmitter)
In analytic form: y = y(u)
where: u is the measured variable
y is the output signal
Example:
in graphic form: 
September 11, 2019
Process Instrumentation and Control - Prof. M. Miccio

9. GENERAL PROPERTIES OF SENSORS
SENSITIVITY
It is defined as the quotient of differences:
S(y) = Δy/Δu
RESOLUTION
It is the smallest change of the measured variables which the sensor can detect on the output signal y
NOTE: the resolution is usually considered on the whole measuring range of the instrument
SENSITIVITY THRESHOLD
It is the instrument resolution at the minimum of its measuring range.
September 11, 2019
Process Instrumentation and Control - Prof. M. Miccio

10. Process Instrumentation and Control - Prof. M. Miccio
HYSTERESYS
It corresponds to the maximum difference between values of the output signal in going and return way in calibration procedure.
It is expressed as a percentage of the full scale (% f.s.).
September 11, 2019
Process Instrumentation and Control - Prof. M. Miccio

11. DYNAMIC CHARACTERISTIC
The dynamic characteristic is a characteristic of the instrument sensor that describes how the instrument responds to a variation in the magnitude of the measured quantity. The dynamic characteristic is expressed by a characteristic time called response time.
It depends on the sensor, on the assembling, etc.
EX.: 
Dynamic characteristic representing the “step change response” of a thermometer
Static error
TIME
Other dynamic properties sometimes used are:
Transfer function:
Bandwidth
from Magnani, Ferretti e Rocco (2007)
September 11, 2019
Process Instrumentation and Control - Prof. M. Miccio

12. SENSORS Classifications
Function and measured variable (T, P, ...)
Based on the physical principle and the related technology adopted (e.g.: optic, piezoelectric, ...)
Based on end use or application
Based on energetic behavior:
active sensor: it converts the energy of the input signal without the aid of external supplier (e.g.: the photovoltaic cell is active because it directly changes the energy of light in electrical energy)
passive sensor: it needs energy from an external supplier to convert the input signal
Smart sensors NEW !
Soft sensors NEW !
September 11, 2019
Process Instrumentation and Control - Prof. M. Miccio 12

13. Process Instrumentation and Control - Prof. M. Miccio
SMART SENSOR
It indicates a more "intelligent and gifted" measuring device compared to a traditional sensor equipped with a transducer, able to:
process a signal into a digital one
transmit information to the external environment as digital signals
have internal redundancy circuits
memorize and provide the configuration, tuning and operating parameters
other auxiliary functions
September 11, 2019
Process Instrumentation and Control - Prof. M. Miccio

14. Process Instrumentation and Control - Prof. M. Miccio
SOFT or VIRTUAL SENSOR
Definition
A mathematical model, correlating difficultly measured quality variables with the frequently and easily measured process variables
Purpose of soft sensor
real-time predictions of the quality variables, monitor processes, design tighter control, fault detection and diagnosis.
from Biao Huang,o H Presentation at ISA Fort McMurray 04/18/11
September 11, 2019
Process Instrumentation and Control - Prof. M. Miccio

15. Process Instrumentation and Control - Prof. M. Miccio
SOFT or VIRTUAL SENSOR
Properties of soft sensor
low cost alternative of expensive online analyzer
easily implemented on existing hardware and no additional investment
provide real-time estimation of quality variable, handling time delay and slow sampling rate of lab data
from Biao Huang,o H Presentation at ISA Fort McMurray 04/18/11
September 11, 2019
Process Instrumentation and Control - Prof. M. Miccio

16. Process Instrumentation and Control - Prof. M. Miccio
SOFT or VIRTUAL SENSOR
Definitions
Soft sensor is a common name for a software-implemented algorithm where several measurements are processed together. There may be dozens or even hundreds of measurements. The interaction of the measurement signals can be used for calculating new quantities that can not be measured.
Soft sensors or inferential calculators are operators’ virtual eyes.
Soft sensors create windows to a process where physical equivalents are unrealistic or even impossible.
Sensor output can be a control signal, advisory information for operators, predictions of product quality, information on process faults or outliers in data, etc.
from Antanas Verikas “Soft Sensors for Monitoring”
September 11, 2019
Process Instrumentation and Control - Prof. M. Miccio

17. SOFT or VIRTUAL SENSOR An Example
September 11, 2019
Process Instrumentation and Control - Prof. M. Miccio

18. Process Instrumentation and Control - Prof. M. Miccio
SOFT or VIRTUAL SENSOR
Techniques
Neural networks (NN)
Neuro-fuzzy systems
Kernel methods (support vector machines)
Multivariate statistical analysis
Data fusion (Dempster-Shafer theory, for example)
Image analysis
from Antanas Verikas “Soft Sensors for Monitoring”
September 11, 2019
Process Instrumentation and Control - Prof. M. Miccio

19. Process Instrumentation and Control - Prof. M. Miccio
SENSOR SELECTION
Selection criteria
Measuring range and span
Accuracy, repeatability, sensitivity and resolution
Rangeability
Dynamic characteristic
Reliability
Costs (purchase, installation, maintenance)
Installation problems and hazard
Construction material related to the fluid properties
September 11, 2019
Process Instrumentation and Control - Prof. M. Miccio 19

20. SENSORS Measured process variables
Temperature
Pressure
Flow rate
Level
stream composition pH
dissolved oxygen
Humidity
Turbidity
Opacity
. . .
September 11, 2019
Process Instrumentation and Control - Prof. M. Miccio 20