教學大綱與進度

課程基本資料：

學年期	課號	課程名稱	階段	學分	時數	修	教師	班級	人	撤	備註
102-2	190338	預測型診斷維護與監督	1	3.0	3	★	劉天一	機電所 製科所	9	0	製科所、機電所合開

教學大綱與進度：

教師姓名	劉天一
Email	liut@csus.edu
最後更新時間	2014-02-27 14:24:00
課程大綱	本課程介紹預測型診斷、維護、與監督之原理與應用。課程內容包括預測型診斷、維護、與監督所需之儀器，儀器所需之性能，數據獲取與訊號分析，特徵選擇以進行決策，智慧型技術在預測型診斷、維護、與監督上之應用。 This course introduces principles and applications of predictive diagnosis, maintenance, and monitoring in industry. The course contents include instrumentation for predictive diagnosis, maintenance, and monitoring; characteristics of the instrumentation; data acquisition and signal analysis; feature selection for decision making; intelligent techniques for predictive diagnosis, maintenance, and monitoring.
課程進度	Week Lecture 1. Introduction to predictive diagnosis, maintenance, and monitoring 2. Instrumentation for predictive diagnosis, maintenance, and monitoring 3. Characteristics of instrumentation for predictive diagnosis, maintenance, and monitoring 4. Contact measurement methods for predictive diagnosis, maintenance, and monitoring 5. Noncontact measurement methods for predictive diagnosis, maintenance, and monitoring 6. Errors and error analysis in predictive diagnosis, maintenance, and monitoring 7. Data acquisition system for predictive diagnosis, maintenance, and monitoring 8. Signal analysis for predictive diagnosis, maintenance, and monitoring 9. Wave distortion in predictive diagnosis, maintenance, and monitoring 10. Anti-aliasing for predictive diagnosis, maintenance, and monitoring 11. Feature selection for predictive diagnosis, maintenance, and monitoring 12. Euclidean distance measure for two states in feature selection 13. Euclidean distance measure for multiple states in feature selection 14. Sequential forward search for feature selection 15. Intelligent technique for two states in predictive diagnosis, maintenance, and monitoring 16. Intelligent technique for multiple states in predictive diagnosis, maintenance, and monitoring 17. Case Studies 18. Case Studies
評量方式與標準	Course Requirements: 1. Successful completion of three quizzes 2. Successful completion of two exams 3. Successful completion of semester project Grading: Quizzes 15% (Three quizzes. No make-up for any quiz) Exams 60% (Two exams. No make-up for any exam) Semester Project 25% (Late report is not acceptable)
使用教材、參考書目或其他	【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】 使用外文原文書：　 References: Books: 1. D. Wang, M. Yu, C.B. Low, and S. Arogeti, “Model-based Health Monitoring for Hybrid Systems,” Springer, 2013 2. Rolf Isermann, “Fault-Diagnosis Applications: Model-based Monitoring: Actuators, Drives, Machinery, Plants, Sensors, and Fault-tolerant Systems,” Springer, 2011 3. Jean-Claude Trigeassou, “Electrical Machines Diagnosis,” John Wiley & Sons, 2011 4. Richard S. Figliola, Donald E. Beasey, “Theory and Design for Mechanical Measurements,” John Wiley & Sons, 2011 5. Lihui Wang, Robert X. Gao, “Condition Monitoring and Control for Intelligent Manufacturing,” Springer, 2006 Journal Papers: 1. Tien-I Liu, Junyi Lee, George Liu, and Zhang Wu, “Monitoring and Diagnosis of Tapping Process for Product Quality and Automated Manufacturing,” International Journal of Advanced Manufacturing Technology, Vol. 64, Issue 5, pp. 1169-1175, 2013 2. T.I. Liu, A. Kumagai, Y.C. Wang, S.D. Song, and J. Lee, "On-Line Monitoring of Boring Tools for Control of Boring Operations," International Journal of Robotics and Computer Integrated Manufacturing, Volume 26, Issue 3, pp. 230-339, 2010 3. Akihiko Kumagai, Tien-I Liu, and Paul Hozian, “Control of Shape Memory Alloy Actuators with A Neuro-Fuzzy Feedforward Model Element,” Journal of Intelligent Manufacturing, Volume 17, pp. 45-56, 2006 4. Tien-I Liu, Farhad Ordukhani, Dipak Jani, “Monitoring and Diagnosis of Roller Bearing Conditions Using Neural Networks and Soft Computing," International Journal of Knowledge-Based and Intelligent Engineering Systems, Volume 9, No. 2, pp. 149-157, 2005 5. W. He, Y.F. Zhang, K.S. Lee, and T.I. Liu, “Development of a Fuzzy Neuro System for Parameter Resetting of Injection Molding,” ASME Journal of Manufacturing Science and Engineering, Vol. 123, No. 1, pp. 110-118, 2001
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