
Ternopil Ivan Puluj National Technical University

Каф. комп'ютерних систем та мереж
Fundamentals of instrumentation and information-measuring systems
syllabus
1. Educational programs for which discipline is mandatory:
# | Educational stage | Broad field | Major | Educational program | Course(s) | Semester(s) |
---|---|---|---|---|---|---|
1 | bachelor's | 12. Інформаційні технології | 123. Комп’ютерна інженерія (бакалавр) | 1 | 2 |
2. The course is offered as elective for all levels of higher education and all educational programs.
4. Information about the course |
|
---|---|
Study hours structure |
Lectures: 18 Practical classes: 0 Laboratory classes: 36 Amount of hours for individual work: 51 ECTS credits: 3.5 |
Teaching language | english |
Form of final examination | credit |
Link to an electronic course on the e-learning platform of the university | https://dl.tntu.edu.ua/bounce.php?course=4423 |
5. Program of discipline
Description of academic discipline, its goals, subject of study and learning outcomes
The purpose of the discipline is to acquaint students with the basics of metrology, modern instrumentation, and information-measurement systems. A student has to demonstrate such learning outcomes on the discipline:
• comprehension of the concept of an error of a measurement and measurement uncertainty
• knowledge of common error sources and their classification
• knowledge of methods of systematic and random error reduction
• comprehension of measurement channel concept
• knowledge of typical types of measurement sensors and instruments
• comprehension of the concept of an error of a measurement and measurement uncertainty
• knowledge of common error sources and their classification
• knowledge of methods of systematic and random error reduction
• comprehension of measurement channel concept
• knowledge of typical types of measurement sensors and instruments
Contents of the academic discipline
Lectures (titles/topics)
1. Basic concepts of metrology.
Fundamental, applied and legal metrology. Traceability. Quantities and units.
2. Accuracy, repeatability and precision.
3. Errors representation.
Absolute, relative and reduced error.
4. Errors classification.
Random and systematic errors. Additive, multiplicative errors, and nonlinearity.
5. Systematic error cancellation.
Method of substitution. Sign compensation. Error contraposition. Gauss double weighting. Calibration.
6. Statistical approach to metrology. Uncertainty. Error distribution function. Confidence interval.
7. Components of measuring channel.
Sensors, transducers, measures.
8. Analog to digital converters.
Quantization and discretization. Nyquist–Shannon sampling theorem. Under- and oversampling. ADC types and properties.
9. Typical sensors: current, temperature, force sensors. Current shunts, Hall current sensors, current clamps, RTD, thermistors, thermocouples, IC temperature sensors, strain gages.
10. Light sensors: photoresistors, photodiodes, CCD and CMOS sensors
11. Smart sensors.
12. Measurement of electrical quantities. Voltmeters, ammeters, ohmmeters, LC-meters.
13. Oscilloscopes
14. Spectrum analyzers
Fundamental, applied and legal metrology. Traceability. Quantities and units.
2. Accuracy, repeatability and precision.
3. Errors representation.
Absolute, relative and reduced error.
4. Errors classification.
Random and systematic errors. Additive, multiplicative errors, and nonlinearity.
5. Systematic error cancellation.
Method of substitution. Sign compensation. Error contraposition. Gauss double weighting. Calibration.
6. Statistical approach to metrology. Uncertainty. Error distribution function. Confidence interval.
7. Components of measuring channel.
Sensors, transducers, measures.
8. Analog to digital converters.
Quantization and discretization. Nyquist–Shannon sampling theorem. Under- and oversampling. ADC types and properties.
9. Typical sensors: current, temperature, force sensors. Current shunts, Hall current sensors, current clamps, RTD, thermistors, thermocouples, IC temperature sensors, strain gages.
10. Light sensors: photoresistors, photodiodes, CCD and CMOS sensors
11. Smart sensors.
12. Measurement of electrical quantities. Voltmeters, ammeters, ohmmeters, LC-meters.
13. Oscilloscopes
14. Spectrum analyzers
Laboratory classes (topics)
1. Quantities and units
2. Errors calculations. Measurement result representation
3. Systematic error cancellation
4. Histogram plotting.
5. ADC and aliasing effects.
6. ADC error budget calculation
7. Analog to digital conversion. Measuring channel calibration
8. Measurement of electrical quantities
9. Use of oscilloscope
10. Use of spectrum analyzers
2. Errors calculations. Measurement result representation
3. Systematic error cancellation
4. Histogram plotting.
5. ADC and aliasing effects.
6. ADC error budget calculation
7. Analog to digital conversion. Measuring channel calibration
8. Measurement of electrical quantities
9. Use of oscilloscope
10. Use of spectrum analyzers
Learning materials and resources
1. CGM 200:2012 International vocabulary of metrology – Basic and general concepts and associated terms (VIM) 3rd edition., CGM 2012
2. The International System of Units, Organisation Intergouvernementale de la Convention du Mètre, 2006
3. Metrology in Industry: The Key for Quality / edited by French College of Metrology, ISTE Ltd, 2006. ISBN-13: 978-1-905209-51-4
4. The Physics of Metrology - All About Instruments - A. Hebra (Springer, 2010)
5. JCGM 100:2008 Evaluation of measurement data — Guide to the expression of uncertainty in measurement, CGM 2012
6. JCGM 106:2012 Evaluation of measurement data – The role of measurement uncertainty in conformity assessment
2. The International System of Units, Organisation Intergouvernementale de la Convention du Mètre, 2006
3. Metrology in Industry: The Key for Quality / edited by French College of Metrology, ISTE Ltd, 2006. ISBN-13: 978-1-905209-51-4
4. The Physics of Metrology - All About Instruments - A. Hebra (Springer, 2010)
5. JCGM 100:2008 Evaluation of measurement data — Guide to the expression of uncertainty in measurement, CGM 2012
6. JCGM 106:2012 Evaluation of measurement data – The role of measurement uncertainty in conformity assessment
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