研究生: |
鍾朝恭 Chaur-gong Jong |
---|---|
論文名稱: |
貝氏網路於水力發電系統故障診斷分析之應用-以石門水庫水力發電系統為例 Bayesian-Network-Based For Hydraulic Power System Fault Diagnosis--Shihmen Reservoir Hydraulic Power Systems For Case Study |
指導教授: |
呂守陞
Sou-Sen Leu |
口試委員: |
潘乃欣
none 周瑞生 none 邱永芳 none 楊偉甫 none |
學位類別: |
博士 Doctor |
系所名稱: |
工程學院 - 營建工程系 Department of Civil and Construction Engineering |
論文出版年: | 2012 |
畢業學年度: | 100 |
語文別: | 中文 |
論文頁數: | 170 |
中文關鍵詞: | 貝氏網路 、韋伯分配 |
外文關鍵詞: | Baysian Network, Weibull Distribution |
相關次數: | 點閱:468 下載:10 |
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目前水庫設施故障診斷多以檢核表進行評估,其成果與品質受限於檢測人員的經驗與經歷,無法達到客觀性判斷及預知維修之目標。有鑑於此,本研究首先以韋伯分配(Weibull Distribution)推求系統可靠度及整體壽命分配,並藉由專家學者及歷史實際故障維修統計資料建立多狀態失誤樹(Multi-State Fault Tree),除先利用失誤樹分析(Fault Tree Analysis, FTA)進行頂事件及各中間事件故障診斷外,同時將該多狀態失誤樹轉換成貝氏網路(Bayesian Network, BN),並加入專家經驗及意見導入節點間橫向連結及權重,接著利用AgenaRisk軟體計算建立條件機率表(Condition Probability Table, CPT)及所建立的貝氏網路作為模型進行故障診斷,同時以現有營運中之石門水庫三部水力發電系統作為分析及驗證對象,經分析比對貝氏網路計算結果與韋伯分配、失誤樹分析、歷史統計資料及系統故障大修後實際運轉統計之平均故障間隔時間(Mean Time Between Failure, MTBF)相符,顯示本研究由多狀態失誤樹轉換成貝氏網路架構,配合導入專家經驗之橫向連結及權重所建立之貝氏網路模型具有合理性與可用性,可作為日後水力發電系統故障診斷脆弱環節及研訂有效維修策略之用。
Current fault diagnosis of reservoir facilities relies mostly on check-list evaluation. The results and qualities of evaluation are limited by experiences and abilities of the evaluators, which may not achieve the goal of systematic assessment in a consistent manner. To overcome the limitation of the traditional approach, We first use the Weibull distribution to calculate the system failure process and the failure distribution, and then this research develops a fault diagnosis and evaluation system for reservoir facility by utilizing multi-state Fault-Tree Analysis (FTA) technique, in conjuction with Bayesian Networks (BN) which incorporate expert experiences through lateral linkages among BN nodes and weighting factors. The system has been used to analyze and verify against three hydro-power systems at the Shihmen reservoir currently in operation. It was found that through BN analysis the fault trend is consistent to that from the Weibull distribution and FTA. This indicates that the transformation of a multi-state Fault-Tree (FT) into BN is reasonable and practical. Based upon the analysis of BN by inputting prior information of the hydro-power systems, the probabilities of fault occurrences and the sensitive factors are effectively computed. Proper preventive maintenance strategies can then be established based upon the BN outputs.
中文文獻
1. 財團法人台灣營建研究院(2002),「公共工程延壽政策及相關技術之探討」,行政院公共工程委員會專案研究計劃PCC-91-研-02。
2. 中興工程顧問股份有限公司(2008),「水庫安全風險管理之研究(2/2)成果報告」,經濟部水利署委辦研究計畫。
3. 國立台灣大學水工試驗所(2004),「水壩安全檢查最佳次序及周期之建立(2/2)」,經濟部水利署委辦研究計畫。
4. 台灣電力股份有限公司(2008修正),「水力發電機操作及維護手冊與石門水力發電機操作標準作業」,台灣電力股份有限公司編制。
5 . 林惠玲、陳正倉(2003二版),「應用統計學」,雙葉書廊有限公司。
6. 王少萍(2000),「工程可靠性」,北京,北京航空大學出版社。
7. 曾聲奎、趙廷弟、張建國、康銳、石君(2001),「系統可靠性設計分析教程」,北京,北京航空航天大學出版社。
8. 曹晉華、程侃(2006),「可靠性數學引論」,北京,北京高等教育出版社。
9. 徐久軍、嚴志軍、朱新河、嚴立(2000),「機械可靠性與維修性」,大連,大連海事大學出版社。
10. 茆詩松、湯銀才、王玲玲(2008),「可靠性統計」,北京,北京高等教育出版社。
11. 陳甄婷(2010),「失誤樹分析轉換成貝氏網路之研究—以水力發電系統引水路失效為例」,國立台灣科技大學營建工程系碩士論文。
12. 林俊甫、徐懷祖、邱龍興(2007),「飛彈彈頭之故障樹分析」,中華民國第七屆可靠度與維護度技術研討會論文集,第319-328頁。
13. 李文瑞(1984),「FTA 技術在系統可靠度應用之硏究」,國立台灣科技大學工業管理系碩士論文。
14. 方鈞(1989),「以故障樹分析技術探討如何防止核三廠主飼水系統設備故障所造成的跳機」,台電核能月刊,第82期,第 243-248頁。
15. 林正宗(2003),「油槽區設施安全之探討」,國立高雄第一科技大學環境與安全衛生工程系碩士論文。
16. 江旺宗(2006),「營造業墜落意外事件模式及相關勞安法規之探討」,國立高雄第一科技大學營建工程系碩士論文。
英文文獻
17. Hadipriono, F. C. (1992), “Expert System for Construction Safety. I: Fault-Tree Models”, Journal of Performance of Constructed Facilities, Vol.6, No.4, pp.242-266.
18. Krasich, Milena (2000), “Use of Fault Tree Analysis for Evaluation of System Reliability Improvements in Design Phase”, Proceedings of the Annual Reliability and Maintainability Symposium, Los Angeles, CA, USA, pp.1-7.
19. AgenaRisk 5.0, User Manual (2010), www.agenarisk.com.
20. Bobbio, A.; Portinale, L.; Minichino, M.; Ciancamerla, E. (1999), “Comparing Fault Trees and Bayesian Networks for Dependability Analysis”, Lecture Notes in Computer Science, Computer Safety, Reliability and Security, Vol.1698, pp.310-322.
21. Bobbio, A.; Prauzy, A.; Minichino, M. (2001), “Improving the Analysis of Dependable Systems by Mapping Fault Tree into Bayesian Network”, Reliability Engineering and System Safety, Vol.71, No.3, pp249-260.
22. Ebeling, Charles E. (1997), Reliability and Maintainability Engineering, McGraw-Hill International Editions.
23. Norman, E.F.; Neil, Martin; Jose Galan Caballero(2007), “Using Ranked Nodes to Model Qualitative Judgments in Bayesian Networks”, IEEE Transactions on Knowledge and Data Engineering, Vol. 19, No. 10, pp.1420-1432.
24. FERC (2005), “Dam Safety Performance Monitoring Program” , Chapter 14, Federal Energy Regulatory Commission, Washington, DC, USA .
25. Qian, Gang; Zhong, Shengguo; Cao, Longhan; (2005), “Bayesian Network based on a Fault Tree and its Application in Diesel Engine Fault Diagnosis” , ICMIT 2005:Control Systems and Robotics, Proc. of SPIE Vol. 6042, 60421P, pp.1-6.
26. Hartford, D.N.D. and Baecher, G.B. (2004), Risk and Uncertainty in Dam Safety, Thomas Telford, Ltd, London, UK.
27. Boudali, H. and Dugan, J.B. (2005), “A Discrete-time Bayesian Network Reliability Modeling and Analysis Framework”, Reliability Engineering & System Satefy, Vol.87, No.3, p p.337-349.
28. Hillson, D.A. (2005), “Describing Probability the Limitations of Natural Language”, Proceedings of PMI Global Congress 2005-EMEA, No.PMB02, Edinburgh, UK, May, pp.23-25.
29. Sigurdsson, J.H.; Walls, L.A.; Quigley, J.L. (2001), “Bayesian Belief Nets for Managing Expert Judgement and Modeling Reliability”, Quality Reliability Engineering International, Vol.17, pp.181-190.
30. Kemp-Benedict (2008), Elicitation Techniques for Bayesian Network Models, Stockholm Environment Institute, WP-US-0804.
31. Leemis, Lawrence M. (1995), Reliability: Probabilistic Models and Statistical Methods, Prentice-Hall International Editions.
32. Liu, Xiao; Li, Haijun; Li, Lin (2008), “Building Method of Diagnostic Model of Bayesian Networks Based on Fault Tree” , Seventh International Symposium on Instrumentation and Control Technology, Sensors and Instruments Computer Simulation, and Artificial Intelligence, Proc. of SPIE Vol. 7127, 71272c, pp.1-6.
33. Looke, R.M. and Goossens, L.H.J (2000), Procedures Guide for Structured Expert Judgement, Report EUR 18820, European Commission, Brussels, Belgium/Luxembourg.
34. Fenton, N. and Neil, M. (2004), “Combining Evidence in Risk Analysis Using Bayesian Network”, Safety Critical Systems Club Newsletter, Vol.13, No.4, pp.1-6.
35. O’connor, Patrick D.T. (2005), Practical Reliability Engineering, John Wiley & Sons, LTD, Fourth Edition.
36. Tobias, Paul A. and Trindade, Davidc (1995), Applied Reliability, International Thomson. Gmbh Publishing, Second Edition.
37. Kales, Paul (2006), Reliability for Technology, Engineering, and Management, Pearson Education Taiwan, Ltd.
38. Doguc, Ozge and Ramirez-Marquez, Jose Emmanuel (2009), “An Efficient Fault Diagnosis Method for Complex System Reliability”, 7th Annual Conference on System Engineering Research (CSER 2009) .
39. Ross, Sheldon M. (2003), Introduction to Probability Models, Eighth Edition , Academic Press , An Imprint of Elsevier Science﹐.
40. RAO, S.S. (2002), Reliability-Based Design, McGraw-Hill International Editions Mechanical Engineering Series.
41. Graves, T.L.; Hamada, M.S.; Klamann, R.; A. Koehler, A.; Martz, H.F. (2007), “A fully Bayesian approach for combining multi-level information in multi-state Fault Tree quantification,” Journal of Reliability Engineering and System Safety. Vol.92, No.10, pp.1476-1483.
42. Franke, U.; Flores, W.R.; Johnson, P. (2009), “Enterprise Architecture Dependency Analysis Using Fault Trees and Bayesian Networks”, Proc. 42nd Annual Simulation Symposium (ANSS), March, San Diego, USA, pp.209-216.
43. William Q. Meeker and Luis A. Escobar (1998),“Statistical Methods for Reliability Data” , A Wiley-Interscience Publication John Wiley & Sons, Inc.