22MDMSPI - Digital Measurements and Signals in Process Engineering
Course specification | ||||
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Course title | Digital Measurements and Signals in Process Engineering | |||
Acronym | 22MDMSPI | |||
Study programme | ||||
Module | ||||
Lecturer (for classes) | ||||
Lecturer/Associate (for practice) | ||||
Lecturer/Associate (for OTC) | ||||
ESPB | 4.0 | Status | ||
Condition | None | Облик условљености | ||
The goal | The goal of the advanced course in digital measurements and signals in process engineering is for students to achieve basic knowledge of digital measurement systems which are used for acquisition, analysis and data processing, as well as to achieve an understanding of how different parts of measurement systems can be used to measure non-electrical quantities through electrical means. | |||
The outcome | After completing and passing the exam, students will be able to perform statistical data processing through the use of software tools, to apply different signal analysis and noise reduction techniques, as well as be able to choose and apply appropriate sensors and measurement systems in process engineering. | |||
Contents | ||||
Contents of lectures | Statistical analysis of data acquired through measurements. Measuring non-electrical quantities through electrical means - sensors. Systems for data acquistion - A/D and D/A convertors. Dynamic measurements. Signal spectrum and discrete Fourier transform. Digital signal processing and noise filtering techniques. Computer systems for measurements and process control (SCADA). | |||
Contents of exercises | Practical lessons are carried out in the computer lab through use of different software packages (Python, LabView, Origin, etc.). The analysis of data acquired through measurements. Signal spectrum analysis. Random noise and noise filtration. Measuring non-electrical quantities through electric means. Measurements and process control in real-time. | |||
Literature | ||||
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Number of hours per week during the semester/trimester/year | ||||
Lectures | Exercises | OTC | Study and Research | Other classes |
2 | 2 | |||
Methods of teaching | Lectures, practical classes in the computer laboratory, consultations | |||
Knowledge score (maximum points 100) | ||||
Pre obligations | Points | Final exam | Points | |
Activites during lectures | Test paper | 25 | ||
Practical lessons | Oral examination | |||
Projects | ||||
Colloquia | ||||
Seminars | 20 |