Course Syllabus

Course Information：

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Spring Semester Year 2024	328178	Fault-Diagnosis Systems	1	3.0	3	★	C.-S.Huang	GEE IEECSG	9	0	電機所和電資外生所合開

Course Plan：

Instructor	C.-S.Huang　Office Hours
Email	cshuang@mail.ntut.edu.tw
Last Updated	2024-04-25 14:58:03
Course Objective	This class starts with an introduction to tasks and terminologies of supervision and fault management. The following is a rough description of the material covered in this class. 1. Reliability, Availability and Maintainability 2. Fault Modelling approaches 3. Fault detection methods 4. Fault diagnosis approaches 5. Fault-tolerant system design
Course Schedule	Week 1: Introduction, Supervision and fault management of processes — tasks and terminology Week 2: Reliability, Availability and Maintainability (RAM) Week 3: Safety, Dependability and System Integrity Week 4: Process Models and Fault Modelling Week 5: Signal models, Fault detection with limit checking Week 6: Fault detection with signal models Week 7: Fault detection with process-identification methods Week 8: Midterm Week 9: Fault detection with parity equations Week 10: Fault detection with state observers and state estimation Week 11: Fault detection of control loops Week 12: Fault detection with Principal Component Analysis (PCA) Week 13: Comparison and combination of fault-detection methods Week 14: Diagnosis procedures and problems Week 15: Fault diagnosis with classification methods Week 16: Final Week 17: Fault diagnosis with inference methods (online) Week 18: Fault-tolerant design, Fault-tolerant components and control (online)
Evaluation and grading policy	Midterm: 40%, Final: 40%, Participation: 20%.
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes Textbook: Isermann, Rolf, "Fault-Diagnosis Systems: An Introduction from Fault Detection to Fault Tolerance," Springer, 2006.
The access to curricular consultation	Contact me via: cshuang @ntut.edu.tw.
The course corresponds to the SDGs
Does the course incorporate AI
Note	The courses on week 17 and 18 will be offered online via Microsoft Teams in response to the Notice from the University: https://oaa.ntut.edu.tw/p/406-1008-136158,r11.php?Lang=zh-tw The Microsoft Teams meeting link is: https://pse.is/5v8dhh In response to Covid-19, the teaching contents and the grading/assessments may be adjusted, and the course will be offered online. (The link will be posted in Taipei Tech i-School Plus) Contact me via: cshuang @ntut.edu.tw.