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Smart measurement transducers - course description

General information
Course name Smart measurement transducers
Course ID 06.5-WE-ELEKTP-SMT-Er
Faculty Faculty of Computer Science, Electrical Engineering and Automatics
Field of study Electrical Engineering
Education profile academic
Level of studies First-cycle Erasmus programme
Beginning semester winter term 2019/2020
Course information
Semester 5
ECTS credits to win 5
Course type optional
Teaching language english
Author of syllabus
  • dr hab. inż. Wiesław Miczulski, prof. UZ
Classes forms
The class form Hours per semester (full-time) Hours per week (full-time) Hours per semester (part-time) Hours per week (part-time) Form of assignment
Lecture 30 2 - - Exam
Laboratory 30 2 - - Credit with grade

Aim of the course

  • acquaint students with the metrological properties of the smart measurement transducers (IMT) and error correction methods,
  • developing the practical skills in the range of analysing the metrological properties of the IMT.

Prerequisites

Fundamentals of metrology, Metrology, Fundamentals of electronics and power electronics, Computer-aided design.

Scope

General characteristics of intelligent measurement transducers. Definition and classification of intelligent measurement transducers. Structure, basic function blocks and operation algorithms. Basic properties of intelligent measurement transducers.

Metrological properties of selected transducer function blocks. Metrological properties of: input circuits of electrical transducers, selected sensors and conditioners, function operators (averaging circuits, analog filters, multipliers, RMS converters, analogue switches and multiplexers, sample and hold (S/H) analog circuits and others).

Methods of error correction. Factors affecting the value of measurement errors. Methods of zero error, sensitivity and nonlinearity correction. Methods of adaptation of the measuring transducers to the parameters of the processed signals. Classical (programmatic) and neural realization of the reproduction process. Selected examples of intelligent measurement transducers.

Teaching methods

  • Lecture: conventional/traditional lecture with elements of discussion.
  • laboratory: work in the groups, practical excersises.

Learning outcomes and methods of theirs verification

Outcome description Outcome symbols Methods of verification The class form

Assignment conditions

Lecture - passing condition is obtaining positive grade from the exam 

Laboratory – the main condition to get a pass are sufficient marks for all exercises and tests conducted during the semester.

 

Calculation of the final grade: lecture 50% + laboratory 50%

Recommended reading

  1.  Bhargawa S.C: Electrical measuring instruments and measurements. CRC Press, 2012.
  2. Bolikowski J. (red): Essentials of designing of smart measurement transducers of electrical quantities, Monograph Nr 68, WSI, Zielona Gora 1993 (in Polish).
  3.  Fraden J.: Handbook of modern sensors. Springer, 2010.
  4. Rutkowski L.: Computational Intelligence: Methods and Techniques, Springer-Verlag Berlin Heidelberg, 2008.
  5. Vetelino J., Reghu A.: Introduction to sensors. CRC Press, 2010.

Further reading

  1.  Horowitz P., Hill W.: The art of electronics. Cambridge University Press, 2010
  2. Miczulski W., Krajewski M., Sienkowski S., A New Autocalibration Procedure in Intelligent Temperature Transducer, IEEE Transactions on Instrumentation and Measurement, 2019, Vol. 68, iss. 3, s. 895--902.

Notes


Modified by dr hab. inż. Wiesław Miczulski, prof. UZ (last modification: 29-10-2019 19:22)