Learning outcome

After successfully completing the course, the candidate will have achieved the following learning outcomes defined in terms of knowledge, skills and general competence.

Knowledge

The candidate can:

• Describe the function and operation of the main sensors and actuators (control devices) that are part of a process
• Identify the various sensors and actuators types
• Describe the basic characteristics of signals in time and frequency domains
• Interpret signals based on their characteristics in time and frequency domains
• Discuss the safety aspects of a measurement system, such as explosion protection, etc.
• Describe digital modulation
• Explain Fourier transform, z-transform and the design of digital filters

Skills

The candidate can:

• Prepare the necessary basis for, program, implement and test a system that contains sensors and actuators
• Select appropriate sensors, actuators and signal processing methods for a given process
• Estimate the uncertainty of measurement data using statistical concepts such as standard deviation, average values, normal distribution, etc.
• Assemble a measuring system focusing on its sensors, actuators and the processing of signals
• Use Fourier analysis in digital (discrete) form
• Apply z-transform, evaluate and design simple digital filters

General competence

The candidate:

• Can collaborate with other students to complete a project that integrates sensor selection, signal processing and programming
• Can describe the work done through a report and an oral presentation in English
• Is aware of the importance of safety in solution-oriented work

Course Description

The course is divided into two components: One component focuses on instrumentation technology, and the other focuses on digital signal processing.

The main topics in instrumentation technology are:

• Measurement and instrumentation systems
• Basic uncertainty analysis
• Wheatstone bridge
• Selected methods
• Computer-based data acquisition
• EMC
• Ex

The main topics in signal processing are:

• Sampling theorem, folding
• Modulation
• Fourier series, frequency spectra, z-transform
• Using filters

Teaching and Learning Methods

The learning outcomes are ensured through a combination of lectures, laboratory which includes both hardware and software elements, and exercises

Assessment Methods

Written examination: 100%

Individual grades (A – F)

All laboratory reports must be passed in order to take final examination

Minor adjustments may occur during the academic year, subject to the decision of the Dean