Intelligent Monitoring of Engineering Systems
Key Info
Basic Information
- Degree:
- Master
- Semesters:
- Summersemester
- Lecturer:
- Univ.-Prof. Dr.-Ing. Bernd Markert
- Language:
- English
Further Information
Contact
Content
The course curriculum consists of seminar lectures followed by a semester project. During the seminar lectures, the students will receive the necessary theoretical background to independently plan and execute the project in small groups. Consultation hours are offered to discuss challenges and problems arising during the course of the project. Finally, each group presents their achievements and results live and in form of a written report.
Topics
The following topics are covered:
- Sensing
- Signal processing
- Machine learning
- Non-Destructive Testing (NDT)
- Structural Health Monitoring (SHM)
- Data pre- and postprocessing using MATLAB
Further information
Course Requirements
Programming experience, particularly in MATLAB (Python)
Course Objectives
In this course, students shall acquire the following:
Knowledge / Understanding
The students will understand
- the theoretical foundations of structural health monitoring approaches in engineering
- state-of-the-art and current trends in structural health monitoring
- the fundamentals of sensors, filtering methods, and computational intelligence
Abilities / Skills
The students can
- describe and analyze mechanical engineering systems
- extract and monitor relevant system parameters
- apply fundamental methods of structural health monitoring
- transfer their knowledge to new engineering applications in science and industry
- independently plan, advance, and complete projects
Teaching and Learning Methods
- Lecture Notes, Slides
- e-Learning Moodle, PowerPoint, MATLAB
Accompanying literature
Goodfellow, I., Bengio, Y., Courville, A., Deep Learning. MIT Press. 2016.