Prerequisite/Recommended prerequisite for
participation in the module
The module adds to the knowledge obtained in Basic Programming,
Applied Statistics and Probability Theory.
Content, progress and pedagogy of the
module
Learning objectives
Knowledge
- Knowledge on the different sensors available and the
fundamental measuring principles.
- Knowledge on the computer based data acquisition, accuracy and
error handling.
- Understand methodology for design of experiments and test
series and for reduction of ambiguity of experimental results, and
for comparability with model predictions.
- Understand processing methods for analog and digital data
(continuous vs. discrete).
Skills
- Isolate principal measurable parameters.
- Be able to plan experiments in order to get optimal information
compared to the experimental effort.
- Be able to choose the right sensor technology for the problem
at hand.
- Setting up the A/D and D/A converters with commercial programs
or by own programs.
- Isolate principal measurable parameters.
- Basic knowledge on digital image analysis.
Competences
- Be able to plan a laboratory or field experiment and setup
appropriate data acquisition.
- Be able to discuss validity of results and errors of the data
acquired in relation to choice of sensor and analysis
method.
Type of instruction
Lectures, etc. supplemented with project work, workshops,
presentation seminars, lab tests.
Extent and expected workload
Since it is a 5 ECTS project module, the workload is expected to
be 150 hours for the student.
Exam
Exams
Name of exam | Measurement Technology, Data Acquisition, Test and
Validation |
Type of exam | Written or oral exam
Individual oral or written exam |
ECTS | 5 |
Assessment | Passed/Not Passed |
Type of grading | Internal examination |
Criteria of assessment | The criteria of assessment are stated in the Examination
Policies and Procedures |