SylabUZ
Nazwa przedmiotu | Modelling of measurement transducers |
Kod przedmiotu | 06.0-WE-ELEKTD-ModofMeasTrans-Er |
Wydział | Wydział Nauk Inżynieryjno-Technicznych |
Kierunek | Elektrotechnika |
Profil | ogólnoakademicki |
Rodzaj studiów | Program Erasmus drugiego stopnia |
Semestr rozpoczęcia | semestr zimowy 2021/2022 |
Semestr | 2 |
Liczba punktów ECTS do zdobycia | 5 |
Typ przedmiotu | obieralny |
Język nauczania | angielski |
Sylabus opracował |
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Forma zajęć | Liczba godzin w semestrze (stacjonarne) | Liczba godzin w tygodniu (stacjonarne) | Liczba godzin w semestrze (niestacjonarne) | Liczba godzin w tygodniu (niestacjonarne) | Forma zaliczenia |
Wykład | 30 | 2 | - | - | Egzamin |
Laboratorium | 30 | 2 | - | - | Zaliczenie na ocenę |
Aacquaint students with the basic principles of construction of mathematical models of measurement transducers.
Shaping of basic skills in analyzing of sources error primary function blocks measuring transducers.
Shaping of basic skills for conducting simulation research and experimental research measuring transducers.
Measurement transducers
General characteristic of measurement transducers. Characteristic of basic functional measurement transducers blocks. Features distinguishing measurement transducers from previous generation transducers.
General notes about designing and role of mathematical model. The aim and stages of the design process. Sequential-iteration design algorithm. Limitations in the process of designing. Essence and scope of the mathematical modeling.
Fundamentals of models building. Stages of modeling. Analogies between physical phenomena. Methods of creation of mathematical models and neural models. Examples of building models of sensor and hardware analog-to-digital.
Basic elements of transducers and their mathematical models. Mathematical models of input circuits, analogue function modules, S/H and A/D converters. Application of artificial intelligence methods in modeling of measuring transducers.
Application of modeling in selected error correction methods of measuring transducers.
Modeling of reverse processing processes in measuring transducers.
Selected examples of the realization of modern measuring transducers.
Lecture, laboratory exercises.
Opis efektu | Symbole efektów | Metody weryfikacji | Forma zajęć |
Lecture – obtaining a positive grade from exam.
Laboratory – the passing condition is to obtain positive marks from all laboratory exercises to be planned during the semester.
Calculation of the final grade: lecture 50% + laboratory 50%
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3. Miczulski W., Sobolewski Ł., Croonenbroeck C., Neural model of a wind turbine// W: XXI IMEKO World Congress Measurement in Research and Industry. Prague, Czechy, 2015 .- Prague,- ISBN: 9788001057933.
4. Proakis J.G, Manolakis D.G.: Digital Signal Processing. Principles, Algorithms and Aplications, Prentice Hall, 2007.
5. Gajda J., Szyper M.: Modeling and simulation research of measurement systems, Jartek s.c. Krakow 1998 (in Polish).
Zmodyfikowane przez dr hab. inż. Paweł Szcześniak, prof. UZ (ostatnia modyfikacja: 12-07-2021 20:50)