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研究生:王聖尤
研究生(外文):Sheng-Yu Wang
論文名稱:多變項失誤監視系統之使用規則
論文名稱(外文):Run rules for multi-variate monitoring process system
指導教授:張玨庭張玨庭引用關係黃世宏
指導教授(外文):Chuei-Tin ChangShyh-Hong Hwang
學位類別:碩士
校院名稱:國立成功大學
系所名稱:化學工程學系碩博士班
學門:工程學門
學類:化學工程學類
論文種類:學術論文
論文出版年:2002
畢業學年度:90
語文別:中文
論文頁數:143
中文關鍵詞:主值分析法使用規則擴展型卡門濾波器警報邏輯統計程序管制
外文關鍵詞:Principal Component AnalysisExtented Kalman FilterAlarm LogicStatistical Process ControlRun Rules
相關次數:
  • 被引用被引用:0
  • 點閱點閱:277
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  • 下載下載:37
  • 收藏至我的研究室書目清單書目收藏:1
在應用單變項失誤偵測技術(如SPC)的過程中,常利用『使用規則』來提升系統狀態的判定效率,但是多變項失誤監視技術(如PCA)之使用規則至今在文獻中尚未見到任何探討。因此在本論文中,我們提出一套系統化的使用規則建構方法。具體而言,我們利用EKF降低估測數據變異度的優點,以及PCA中投影量各自獨立的特性,依警報邏輯的設計技巧[Tsai and Chang, 1996],發展出可根據線上狀態估測值即時調整使用規則的多變項失誤監視策略,而使系統狀態判斷之期望損失值得以最小化。從利用TE製程模擬程式製造出的數據測試結果中可以發現,本研究所提出的方法不但可以顯著減少傳統監視方法的誤判比例,還可提早在失誤發生初期就偵測出誤源。
In implementing the single-variate process monitoring procedures, such as those adopted for statistical process control (SPC), a set of run rules are often used to facilitate proper assessment of the system states (Bavadas, 1993; Western Electric Company, 1956). However, the run rules of multi-variate monitoring methods, e.g. the principal component analysis (PCA), have never been discussed in the literature. A systematic procedure is thus developed in this work to generate these rules on-line. Specifically, the well-established alarm-logic design techniques (Tsai and Chang, 1996) are adopted to minimize the expected loss of misjudgment in fault detection. Unlike the traditional monitoring approach, the proposed run rules can be adjusted in real time according to state estimates. To enhance alarm accuracy, the EKFs are used to reduce the variation in state estimation. Also, in order to ensure that the alarm variables are mutually uncorrelated, the projections in the principal directions obtained in PCA are adopted for characterizing the system states. The feasibility of the proposed approach has been verified with measurement data produced with the Tennessee-Eastman process simulation program (Downs and Vogel, 1993). The test results show that the multi-variate run rules are not only useful in avoiding spurious alarms, but also effective in detecting incipient abnormal conditions.
第一章 緒論1

第二章 傳統製程監視方法4
2.1 統計程序管制(SPC)4
2.1.1 管制圖(Control Chart)4
2.1.2 使用規則(Run Rules)11
2.1.3 簡例12
2.2 主值分析法15
2.2.1 理論背景15
2.2.2 計算流程23
2.2.3 維度之選擇與簡化28
2.2.4 簡例29
2.3 應用實例31
第三章 多變項失誤監視系統之使用規則61
3.1 警報邏輯的建構方法61
3.2 卡門濾波器(EKF)65
3.3 條件機率之估算69
3.4 實例測試71
3.4.1 警報邏輯的應用-單變項使用規則72
3.4.2 警報邏輯的應用-多變項使用規則77
第四章 結論與展望112
4.1 結論112
4.2 展望112

參考文獻114
附錄116
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[2]Badavas, P. C., Real-Time Statistical Process Control , Prentice-Hall, Inc., Englewood Cliffs, New Jersey(1993).
[3]Downs, J. J., and E. F. Vogel, “A Plant –Wide Industrial Process Control Problem,” Computers Chem. Engng., 17, pp.245(1993).
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[11]Mah, R. S. H., G. M. Stanley, and D. M. Downing, “Reconciliation and Rectification of Process Flow and Inventory Data,” I&EC. Proc. Des. Dev., 15, pp.175 (1976).
[12]Mah, R. S. H., Chemical Process Structu An Engineer’s Manual of Statistical Methods res and Information Flows, Butterworth, Boston (1990).
[13]Nomikos, P., and J. F. MacGregor, “Monitoring Batch Process Using Multiway Principal Component Analysis,” AIChE J., 40, 1361 (1994).
[14]Passano, A. I. et al, ASTM Manual on Quality Control of Material, American Society for Testing Materials, Baltimore(1956).
[15]Raich, A., and A. Cinar, “Diagnosis of Process Disturbances by Statistical Distance in Multivariable Continuous Processes,” AIChE J., 42, 995(1996).
[16]Sharma, S., Applied Multivariate Techniques, John Wiley & Sons, Inc., New York(1996).
[17]Tsai, C. S., and C. T. Chang, “Statistical Operating Strategies for Charging Batch Reactors,” AIChE J., 42, 1304 (1996).
[18]Tsai, C. S., and C. T. Chang, “Optimal Alarm Logic Design for Mass Flow Networks ” AIChE J., 43, 3021 (1997).
[19]Tsai, C. S., and C. T. Chang, “Resilient Alarm Logic Design for Process Networks ,” I&EC Research, 39, 4974 (2000).
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