Selected Chapters of Diagnostics
- Department of Measurement
This course introduces advanced concepts of fault detection, isolation and diagnostics, signal analysis methods for machine condition monitoring, and principles and instrumentation of non-destructive testing, the corresponding advanced signal processing, and self-acting evaluation in order to improve reliability, availability, maintenance, and life-time.
- Syllabus of lectures:
1. Fault-detection and diagnosis methods
2. Fault detection with signal models
3. Fault detection with parity equations
4. Fault detection with observers, estimators, and PCA
5. Combination of fault-detection methods
6. Fault diagnosis with inference methods
7. Diagnosis knowledge representation
8. Condition monitoring - advanced signal analysis
9. Condition monitoring - instrumentation, M2M architectures
10. Condition monitoring - edge computing
11. Non-destructive testing - arrays
12. Non-destructive testing - multichannel processing and analysis
- Syllabus of tutorials:
1. - 13. Individual project - experimental work
14. Presentation of results. Manuscript assessment.
- Study Objective:
The course should give an extensive treatment of special non-destructive testing methods and diagnostic procedures including advanced signal processing methods, signal recognition and classification.
- Study materials:
 Yan, Jihong. Machinery Prognostics and Prognosis Oriented Maintenance Management, John Wiley & Sons, Incorporated, 2015. ISBN: 978-1-118-63872-9
 Rafael Gouriveau, Kamal Medjaher, Noureddine Zerhouni. From Prognostics and Health Systems Management to Predictive Maintenance 1: Monitoring and Prognostics, Wiley-ISTE, Nov 2016. ISBN: 978-1-848-21937-3
 G. Vachtsevanos et al.: Intelligent Fault Diagnosis and Prognosis for Engineering Systems, John Wiley & Sons, Inc. 2006.
 R. Isermann: Fault-Diagnosis Systems, Springer Berlin Heidelberg 2006.
- Further information:
- No time-table has been prepared for this course
- The course is a part of the following study plans: