基于嵌入式的柴油機在線故障診斷系統(tǒng)設計
發(fā)布時間：2018-08-28 10:40
【摘要】：柴油機作為工業(yè)制造、車輛、船舶、采礦的主要動力源,其故障診斷的技術成為近幾年研究的熱點之一。本文設計了一種下位機采集與上位機測試一體化的在線診斷的方法,并通過LMD-SVM算法實現(xiàn)柴油機的故障診斷。本診斷系統(tǒng)的下位機設計,主要應用了信息技術,設計了一種以ARM11內核的S3C6410為處理器、以ADXL345為振動傳感器、以Linux為操作系統(tǒng)的數(shù)據(jù)可存儲的采集裝置,且可以通過串口實現(xiàn)與上位機的數(shù)據(jù)通信。本診斷系統(tǒng)的上位機設計,主要應用了MATLAB工具,利用GUI功能設計了一個用于人機交互的用戶界面,用于振動數(shù)據(jù)的動態(tài)顯示和邏輯控制,并嵌入了LMD-SVM算法,用于模式分類和故障診斷。LMD-SVM算法是將原始信號進行局域均值分解成多個PF函數(shù)分量,求解每個PF函數(shù)的近似熵,并將近似熵組合作為特征向量,先將訓練樣本輸入支持向量機進行訓練,建立SVM數(shù)學模型,再將測試樣本輸入SVM進行模式分類,最終實現(xiàn)故障診斷。最后,以R6105AZLD型號的柴油機為研究對象,選取柴油機的6種工況,搭建柴油機試驗平臺,調試下位機和上位機,實現(xiàn)信號的在線采集,分別用180組測試樣本進行試驗,測試通過率高達91.67%,試驗表明,此方法能基本滿足工程應用。
[Abstract]:As the main power source of industrial manufacture, vehicle, ship and mining, the fault diagnosis technology of diesel engine has become one of the hotspots in recent years. In this paper, an on-line diagnosis method of the integration of lower computer acquisition and upper computer testing is designed, and the fault diagnosis of diesel engine is realized by LMD-SVM algorithm. In the design of the lower computer of the diagnosis system, the information technology is mainly used, and a kind of data acquisition device, which uses S3C6410 of ARM11 kernel as processor, ADXL345 as vibration sensor and Linux as operating system, is designed. And can realize the data communication with the host computer through the serial port. In the design of the upper computer of the diagnosis system, the MATLAB tool is mainly used, and a user interface for human-computer interaction is designed by using the GUI function, which is used for dynamic display and logic control of vibration data, and the LMD-SVM algorithm is embedded. LMD-SVM algorithm is used for pattern classification and fault diagnosis. LMD-SVM algorithm decomposes the local mean of the original signal into several PF function components, solves the approximate entropy of each PF function, and combines the approximate entropy as the eigenvector. The training sample is input into support vector machine to train, the SVM mathematical model is established, then the test sample is input into SVM to classify the pattern, and finally the fault diagnosis is realized. Finally, taking the diesel engine of R6105AZLD model as the research object, selecting six working conditions of the diesel engine, setting up the diesel engine test platform, debugging the lower computer and the upper computer, realizing the on-line acquisition of the signal, the test is carried out with 180 groups of test samples, respectively. The passing rate of the test is up to 91.67. The experiment shows that this method can basically meet the engineering application.
【學位授予單位】：中北大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：TK428
本文編號：2209151
[Abstract]:As the main power source of industrial manufacture, vehicle, ship and mining, the fault diagnosis technology of diesel engine has become one of the hotspots in recent years. In this paper, an on-line diagnosis method of the integration of lower computer acquisition and upper computer testing is designed, and the fault diagnosis of diesel engine is realized by LMD-SVM algorithm. In the design of the lower computer of the diagnosis system, the information technology is mainly used, and a kind of data acquisition device, which uses S3C6410 of ARM11 kernel as processor, ADXL345 as vibration sensor and Linux as operating system, is designed. And can realize the data communication with the host computer through the serial port. In the design of the upper computer of the diagnosis system, the MATLAB tool is mainly used, and a user interface for human-computer interaction is designed by using the GUI function, which is used for dynamic display and logic control of vibration data, and the LMD-SVM algorithm is embedded. LMD-SVM algorithm is used for pattern classification and fault diagnosis. LMD-SVM algorithm decomposes the local mean of the original signal into several PF function components, solves the approximate entropy of each PF function, and combines the approximate entropy as the eigenvector. The training sample is input into support vector machine to train, the SVM mathematical model is established, then the test sample is input into SVM to classify the pattern, and finally the fault diagnosis is realized. Finally, taking the diesel engine of R6105AZLD model as the research object, selecting six working conditions of the diesel engine, setting up the diesel engine test platform, debugging the lower computer and the upper computer, realizing the on-line acquisition of the signal, the test is carried out with 180 groups of test samples, respectively. The passing rate of the test is up to 91.67. The experiment shows that this method can basically meet the engineering application.
【學位授予單位】：中北大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：TK428
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，本文編號：2209151
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