【摘要】：柴油機(jī)作為工業(yè)制造、車輛、船舶、采礦的主要?jiǎng)恿υ?其故障診斷的技術(shù)成為近幾年研究的熱點(diǎn)之一。本文設(shè)計(jì)了一種下位機(jī)采集與上位機(jī)測(cè)試一體化的在線診斷的方法,并通過LMD-SVM算法實(shí)現(xiàn)柴油機(jī)的故障診斷。本診斷系統(tǒng)的下位機(jī)設(shè)計(jì),主要應(yīng)用了信息技術(shù),設(shè)計(jì)了一種以ARM11內(nèi)核的S3C6410為處理器、以ADXL345為振動(dòng)傳感器、以Linux為操作系統(tǒng)的數(shù)據(jù)可存儲(chǔ)的采集裝置,且可以通過串口實(shí)現(xiàn)與上位機(jī)的數(shù)據(jù)通信。本診斷系統(tǒng)的上位機(jī)設(shè)計(jì),主要應(yīng)用了MATLAB工具,利用GUI功能設(shè)計(jì)了一個(gè)用于人機(jī)交互的用戶界面,用于振動(dòng)數(shù)據(jù)的動(dòng)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(hào)進(jìn)行局域均值分解成多個(gè)PF函數(shù)分量,求解每個(gè)PF函數(shù)的近似熵,并將近似熵組合作為特征向量,先將訓(xùn)練樣本輸入支持向量機(jī)進(jìn)行訓(xùn)練,建立SVM數(shù)學(xué)模型,再將測(cè)試樣本輸入SVM進(jìn)行模式分類,最終實(shí)現(xiàn)故障診斷。最后,以R6105AZLD型號(hào)的柴油機(jī)為研究對(duì)象,選取柴油機(jī)的6種工況,搭建柴油機(jī)試驗(yàn)平臺(tái),調(diào)試下位機(jī)和上位機(jī),實(shí)現(xiàn)信號(hào)的在線采集,分別用180組測(cè)試樣本進(jìn)行試驗(yàn),測(cè)試通過率高達(dá)91.67%,試驗(yàn)表明,此方法能基本滿足工程應(yīng)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(xué)位授予單位】：中北大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TK428

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