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研究生:陳振文
研究生(外文):Jenn-Wen Chen
論文名稱:失誤監視技術之研究-擴展型卡門濾波器應用上的問題
論文名稱(外文):Studies on the Fault Monitoring Methods-Issues concerning the Implementation of Extended Kalman Filter
指導教授:張玨庭張玨庭引用關係
指導教授(外文):Chuei-Tin Chang
學位類別:碩士
校院名稱:國立成功大學
系所名稱:化學工程研究所
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:1994
畢業學年度:82
語文別:中文
論文頁數:121
中文關鍵詞:失誤監視系統擴展型卡門濾波器
外文關鍵詞:Fault Monitoring SystemExtended Kalman Filter
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擴展型卡門濾波器(extended Kalman filter,EKF)是常用的失誤偵測與
診斷工具,雖然它的有效性廣受肯定,但在實際應用上仍極有限,這是因
為EKF的參數估計,常會在多誤源的情況下,出現偏差(bias)的現象。因
此,本研究之目的,即探討藉由選擇測量變數以及EKF模式參數的方式,
減少甚致消除估計偏差的可能性。在這一方面,我們計劃延續過去對平行
單參數EKF之失誤可觀測性(fault observability),診斷解析度(
diagno- stic resolution)與偵測點配置策略的研究(Chang et al.
,1993),推廣至以多參數EKF同時對多誤源診斷的問題上。更具體的說,
本研究藉由EKF估測參數與測量變數的選擇,克服EKF應用上估計偏差與併
行計算量過大的問題,並使得失誤監視系統的功能涵蓋多重失誤發生的可
能性。此外,我們也發展適切的定性評量方法,在不須繁冗數學演算分析
的情況下,即可迅速而有效地決定系統可觀測與解析度。而本研究中提出
方法的可靠性,皆經由數值模擬方式驗證無誤。

The extended Kalman filter (EKF) is one of the most popular
model-based techniques for fault detection and diagnosis.
Although its effectiveness has been widely recognized, the
practical applications of EKFs are still very limited. This is
due to the fact that the estimates of EKF are often biased in a
system with multiple faults. Thus, one of the objectives of
this work is to explore the feasibility of reducing or even
eliminating the chance of bias by properly selecting a set of
measurement variables and EKF parameters. In this study, we
have extended the findings of our previous research on fault
observability and diagnostic resolution of a set of parallel
single-parameter EKFs (Chang et al., 1993) to the multiple-
parameter EKFs which are designed to locate more than one fault
origin. Specifically,the problems in implementing EKFs , i.e.
misdiagnosis due to biased estimates and heavy computation load
due to the parallel configuration, have been partially solved
with a selection strategy for the best combinations of sensor
locations and parameters in the EKF models. In addition, the
scope of fault monitoring has been expanded to include the
possibility of simultaneous occurrence of several faults. More
importantly, a simple procedure has been developed to quickly
evaluate the performance of any given system. As a result, it
becomes feasible to construct an optimum fault identification
scheme without extensive computational effort. Finally, it
should be emphasized that reliability of the proposed approach
has been confirmed in numerous simulation studies without
exceptions.

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