本文選題：故障診斷　切入點：粒子濾波　出處：《燕山大學》2014年碩士論文　論文類型：學位論文

【摘要】：電液伺服系統(tǒng)是典型的集機、電、液一體化的復雜精密自動控制系統(tǒng)，，應用極其廣泛，尤其是在功率重量比大，又要求響應速度快的場合應用更為普遍，難以替代。但同時由于元器件的復雜精密和高度集成導致加工難度高，抗污染能力差，故障時有發(fā)生，為此對其進行故障診斷研究具有非常重要的意義。其中基于解析模型的故障診斷方法在解決電液伺服系統(tǒng)的故障診斷問題中得到了廣泛應用，但目前這類方法大多都是采取對系統(tǒng)的工作點附近進行線性化來實現(xiàn)故障診斷，而電液伺服系統(tǒng)本質(zhì)上是一個較強的非線性系統(tǒng)，因此不可避免地會影響故障檢測和診斷的準確性。針對現(xiàn)有方法的不足，以及粒子濾波方法在對非線性非高斯問題的處理顯現(xiàn)出明顯的優(yōu)越性，為此本文提出將基于粒子濾波的故障診斷方法應用到電液伺服系統(tǒng)中去。本文圍繞基于粒子濾波的電液伺服系統(tǒng)故障診斷方法如何實現(xiàn)展開研究，主要研究內(nèi)容和結(jié)論如下： 第一、綜述了電液伺服系統(tǒng)現(xiàn)有故障診斷方法并分析了其優(yōu)缺點，同時還總結(jié)分析了粒子濾波算法的改進研究現(xiàn)狀及其在故障診斷中應用研究現(xiàn)狀； 第二、詳細論述了粒子濾波的基本原理，進而通過實例仿真，對比研究了標準粒子濾波方法與擴展卡爾曼濾波、無跡卡爾曼濾波方法的濾波估計性能，結(jié)果表明，不論是非線性高斯模型還是非線性非高斯模型，粒子濾波方法的濾波精度均高于后面兩種傳統(tǒng)的濾波方法； 第三、對比研究了基于粒子濾波的兩種檢測方法的性能，結(jié)果顯示基于狀態(tài)估計和殘差平滑的故障檢測方法優(yōu)于基于似然函數(shù)的故障檢測方法；同時針對通過殘差并不容易識別故障的類型問題，將基于信息散度的故障識別方法引入，仿真結(jié)果驗證了該方法的有效性； 第四、以電液位置伺服系統(tǒng)為研究對象，對其建立了非線性模型，進而研究了基于粒子濾波狀態(tài)估計和殘差平滑的故障檢測方法和基于信息散度的識別方法應用于對系統(tǒng)典型故障進行檢測與識別，仿真結(jié)果表明兩方法分別能夠及時準確地檢測故障和識別故障類型； 第五、通過液壓缸內(nèi)泄漏故障對基于粒子濾波的故障檢測方法和基于信息散度的故障識別方法進行了實驗研究，實驗結(jié)果表明兩方法切實有效。
[Abstract]:Electro-hydraulic servo system is a typical complex and precise automatic control system with integration of electricity and fluid, which is widely used, especially in situations where the power / weight ratio is large and the response speed is required. It is difficult to replace. But at the same time, due to the complex precision and high integration of components, it is difficult to process, poor anti-pollution ability, and faults occur from time to time. Therefore, it is of great significance to study the fault diagnosis, in which the analytical model based fault diagnosis method has been widely used to solve the problem of electro-hydraulic servo system fault diagnosis. However, at present, most of these methods adopt linearization near the operating point of the system to realize fault diagnosis, and the electro-hydraulic servo system is essentially a strong nonlinear system. Therefore, the accuracy of fault detection and diagnosis will inevitably be affected. In view of the shortcomings of existing methods and the obvious superiority of particle filter in dealing with nonlinear non-#china_person0# problems, In this paper, the fault diagnosis method based on particle filter is applied to the electro-hydraulic servo system. The main contents and conclusions are as follows: (1) this paper focuses on how to realize the fault diagnosis method of electro-hydraulic servo system based on particle filter. First, the existing fault diagnosis methods of electro-hydraulic servo system are summarized, and their advantages and disadvantages are analyzed. At the same time, the research status of particle filter algorithm improvement and its application in fault diagnosis are summarized and analyzed. Secondly, the basic principle of particle filter is discussed in detail, and the estimation performance of standard particle filter, extended Kalman filter and unscented Kalman filter are compared by simulation. Whether the nonlinear Gao Si model or the nonlinear non-#china_person1# model, the filter accuracy of particle filter is higher than the latter two traditional filtering methods. Thirdly, the performance of two detection methods based on particle filter is compared. The results show that the fault detection method based on state estimation and residual smoothing is better than that based on likelihood function. At the same time, the fault identification method based on information divergence is introduced to solve the problem that the fault type can not be easily identified by residual error. The simulation results verify the effectiveness of the method. In 4th, taking electro-hydraulic position servo system as the research object, a nonlinear model is established. Then the fault detection method based on particle filter state estimation and residual smoothing and the method based on information divergence are studied to detect and identify the typical faults of the system. The simulation results show that the two methods can detect faults and identify fault types in time and accurately. In 5th, the fault detection method based on particle filter and fault identification method based on information divergence are studied experimentally by hydraulic cylinder leakage fault. The experimental results show that the two methods are practical and effective.
【學位授予單位】：燕山大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TH137;TH165.3

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