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 and place them in a P & ID diagram
• 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
• Measurement systems and electrical output signals
• Computer-based data acquisition
• Basic statistical methods and uncertainty analysis
• Selected methods
• Dynamic measurement systems

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, practical semester assignments (cases) that include both hardware and software elements, exercises and business visits.

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