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Course content |
Module 1: Fundamentals of Measurement, Sensing and Instrumentation
Definition of measurement and instrumentation, physical variables, common types of sensors; Describe the function of these sensors; Use appropriate terminology to discuss sensor applications; and qualitatively interpret signals from a known sensor type, types of instrumentation, Sensor Specifics, Permanent installations, Temporary installations; Pressure meters, Piezometer, Pressure cells, O-Cell, Sensors, Inclinometers, Strain gauges, Accelerometers, LVDT & Optical Encoder.
Module 2: Sensor Installation and Operation
i) Predict the response of sensors to various inputs; ii) Construct a conceptual instrumentation and monitoring program; iii) Describe the order and methodology for sensor installation; and iv) Differentiate between types of sensors and their modes of operation and measurement and v) Approach to Planning Monitoring Programs, Define target, Sensor selection, Sensor siting, Sensor Installation & Configuration, Advanced topic, Sensor design, Measurement uncertainty.
Module 3: Data Analysis and Interpretation
a) Fundamental statistical concepts, b) Data reduction and interpretation, c) Piezometer, Inclinometer, Strain gauge, etc. d) Time domain signal processing, e) Discrete signals, Signals and noise and f) a few examples of statistical information to calculate are: Average value (mean), On average, how much each measurement deviates from the mean (standard deviation), Midpoint between the lowest and highest value of the set (median), Most frequently occurring value (mode), Span of values over which your data set occurs (range).
Module 4: Frequency Domain Signal Processing and Analysis
Explain the need for frequency domain analysis and its principles; Draw conclusions about physical processes based on analysis of sensor data; Combine signals in a meaningful way to gain deeper insight into physical phenomena, Basic concepts in frequency domain signal processing and analysis, Fourier Transform, FFT (Fast Fourier Transform), Example problems: Noise reduction with filters, Leakage, Frequency resolution.
Module 5: Intelligent Sensors
General Structure of smart sensors & its components, Characteristic of smart sensors: Self calibration, Self-testing & self-communicating, Application of smart sensors: Automatic robot control & automobile engine control.
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Texts/References |
- AS Morris (2001), Measurement and Instrumentation Principles, Butterworth Heinemann, 3rd edition.
- DVS Murthy (2013), Transducers and Instrumentation, PHI, 2nd edition.
- D Patranabis (2003), Sensors and Transducers, PHI, 2nd edition
- S Tumanski (2006), Principle of Electrical Measurement, Taylor & Francis, 1st edition.
- AD Helfrick and WD Cooper (2015), Modern Electronic Instrumentation & Measurement Techniques, Pearson India, 1st edition.
- I Gertsbakh (2010), Measurement Theory for Engineers, Springer, 1st edition.
- AK. Ghosh (2012), Introduction to measurements and Instrumentation, PHI, 4th edition.
- HKP Neubert (2012), Instrument Transducers Oxford University Press, 2nd edition.
- DA Bell (2007), Electronic Instrumentation and Measurements, Oxford University Press, 2nd edition
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