容錯多餘感測系統之即時錯誤鑑別及更正

Abstract

在一個採用多餘感測器構成的感測系統中,錯誤感測器的識別(fault identification)是透過數個多餘(redundant)感測器輸出所組成的關係式“voting equations”來進行。然而當感測器輸出帶有雜訊時,此鑑別方式將造成識別錯誤,進而無法達成“即時”的錯誤感測器鑑別,更無法達成“即時”的錯誤訊號更正。本論文針對此問題,提出一解決方法來達成“即時”的錯誤訊號鑑別及錯誤更正。並將此解決方法以matlab程式模擬和實驗驗證來進行可行性研究。 所提出的解決方法乃是將傳統的錯誤元件的鑑別問題轉化成一非線性的狀態估測(state estimation)問題。如此一來,便可以“即時”的獲得每個感測器的誤差量,並加以補償,達成“即時”之錯誤更正。欲達到此一目的,我們找出可以描述多餘感測系統的動態方程式(dynamic equations)和輸出方程式(output equations),藉由系統的動態方程式和輸出方程式,我們可以檢驗系統的可觀察性(observability)來確保錯誤訊號可以被正確的估測,再建構一狀態估測器(state observer)來估測錯誤訊號。我們所採用的狀態估測器是”記憶褪去式卡曼濾波器(Kalman filter with fading memory)。”估測出感測器輸出的誤差值後,我們採用狀態回授法來進行錯誤感測器的訊號更正,使更正後的感測器可繼續存在於感測系統中運作,以提高系統的輸出的精度。 在matlab的程式模擬中,本方法可以成功的即時估測出錯誤訊號,並加以修正。未來的工作將著重於設計一實驗架構來驗證本方法的可行性。實驗架構初步規劃如下:量測馬達轉動時三個加速規的向心加速度an,與馬達轉速w,藉由旋轉力學公式 公式an=w^2*r,可獲得voting equations,進而構成一個多餘感測器量測系統。再以本論文所提出的演算法來估算每一加速規輸出值的偏差量與修正量,進而驗證本演算法驗證是否可行。

In a sensing system with redundant sensors,fault signal sensor was idenfied through the “voting equations”that was composed of relations of redundant sensors.However,while do sensors have noises,the former method will result in identifying inexactly ,nonreal-time estimation,and nonreal-time compensation.According to this issue,the thesis propose one method to solve this question and to reach real-time fault signal identification and correction.Then this algorithm design will take matlab program to stimulate and implement practical experiment to verify responsibility of this algorithm. We propose a progressive method that convert traditional fault identification method to observation nonlinear state estimation.That is,observation can observe every sensors’ fault signals then compensate these errors to reach real-time fault signal correction.To obtain this goal,we can design dynamic equations and output equations that is depicted redundant sensing system.We can scrutinize the observability of system to ensure fault signals that is estimated exactly .We create a state observer to observe fault signal.The state observer which is taken by ours is “kalman filter with fading memory”.After observer appraised the errors of sensors,we will take state feedback to correct fault signal of sensors.That is to say,we make corrected sensors which still can continue to operate in the sensing system. It is to raise output value precision and reliability of system. To simulate the matlab program,the algorithm of this thesis can evaluate instantaneously fault signals and compensate immediately.The point of this thesis design a realistic system to experiment and affirm this algorithm’s responsibility.To sum it up,we design a revolving mechanism of motor and place three accelerators(sensors) on it.The three accelaerators have been placed on different ratio radius(for example:1:1.5:2).Then we use microcontroller to detect accelerators’ A/D(analog to digital) datas. According normal component equation of curvilinear motion ( an=w^2*r),the three normal equations of curvilinear motion have restrainable relations among them. The three restrainable relations can obtain voting equations and then construct a redundant sensing system(observer).Finally,we collect accelerators’ A/D(analog to digital) datas friom microcontroller and take them to matlab program to validate whether the algorithm’s responsibility of this thesis.