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

Name

Bernd Markert

Institutsleiter, Rektoratsbeauftragter für Alumni

Phone

work
+49 241 80-94600

Email

E-Mail
 

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.