基于BP神經(jīng)網(wǎng)絡的異步電機故障診斷

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目 錄
第一章 緒論………………………………………………………………………1
1.1神經(jīng)網(wǎng)絡……………………………………………………………………… 1
1.1.1 神經(jīng)網(wǎng)絡分類及簡單介紹………………………………………………… 1
1.1.2 BP神經(jīng)網(wǎng)絡…………………………………………………………………………5
1.2異步電動機工作原理及用途………………………………………………… 8
1.3異步電動機常見故障類型及方法…………………………………………… 8
1.3.1異步電動機常見故障類型………………………………………………… 9
1.3.2異步電動機電氣故障分析………………………………………………………………9
1.4電動機故障診斷的主要方法……………………………………………………11
1.4.1基于人工神經(jīng)網(wǎng)絡故障診斷…………………………………………………13
1.4.2基于專家系統(tǒng)故障診斷………………………………………………………13
1.4.3基于信息融合技術(shù)故障診斷…………………………………………………14
1.4.4基于小波變換故障診斷………………………………………………………14

第二章異步電動機在MATLAB中的建模仿真及故障設置……………….16
2.1 BP神經(jīng)網(wǎng)絡在異步電機故障診斷中的應用……………………………………………..15
2.2異步電動機在MATLAB中的建模（頻譜法）………………………………… 16
2.2.1選擇并搭建模塊………………………………………………………………….16
2.2.2模塊參數(shù)設定…………………………………………………………………….19
2.3三相異步電動機故障設置及故障特征提取………………………………………22
第三章BP網(wǎng)絡異步電動機故障診斷實例………………………………….23
3.1 BP神經(jīng)網(wǎng)絡算法的原理……………………………………………………………28
3.1.1人工神經(jīng)元的模型……………………………………………………………… 28
3.1.2 BP 神經(jīng)網(wǎng)絡算法的原理…………………………………………………………28
3.2 BP神經(jīng)網(wǎng)絡的構(gòu)建………………………………………………………………… 29
3.2.1 輸入輸出神經(jīng)元數(shù)確定………………………………………………………… 29
3.2.2.隱含層層數(shù)的確定……………………………………………………………… 29
3.3 BP網(wǎng)絡訓練與測試………………………………………………………………. 30
第四章 總結(jié)與展望…………………………………………………………….40
4.1 總結(jié)……………………………………………………………………………………………40
4.2 展望………………………………………………………………………………………………41
致謝……………………………………………………………………………42
參考文獻………………………………………………………………………43


摘要：近年來由于我國經(jīng)濟迅速發(fā)展，電氣設備的應用范圍逐步由城市轉(zhuǎn)向農(nóng)村,三相異步電動機因其物美價廉的特點，被普遍應用于工業(yè)生產(chǎn)的各個領(lǐng)域。如果電機故障，將給人們的生產(chǎn)和生活造成巨大損失，因此電動機故障診斷具有重要的現(xiàn)實意義。
首先，神經(jīng)網(wǎng)絡，分類的原則，應用和前景進行了介紹，然后，異步電動機的基本原理，故障分類和故障診斷方法。介紹了一種基于BP神經(jīng)網(wǎng)絡模型的故障診斷方法，著重對異步電動機各相接地短路故障,利用FFT頻譜法分析, 將仿真實驗得到的數(shù)據(jù)作為其訓練樣本數(shù)據(jù)。處理與歸一化這些數(shù)據(jù)后，把他們作為神經(jīng)網(wǎng)絡的輸入，經(jīng)過學習與訓練，最終可以識別系統(tǒng)的故障類型。
通過MATLAB軟件，并通過對BP神經(jīng)網(wǎng)絡基本原理的概要介紹，說明建立基于BP網(wǎng)絡的故障診斷架構(gòu)，并通過實驗得到足夠的樣本數(shù)據(jù)來訓練神經(jīng)網(wǎng)絡,，從而實現(xiàn)了對電機的診斷。本文建立的BP神經(jīng)網(wǎng)絡故障診斷系統(tǒng)一種頗具成效的故障診斷方法，技術(shù)也日臻成熟，對于三相異步電動機的故障診斷研究具有重要的參考價值。

關(guān)鍵詞：異步電動機 ； 故障診斷； BP 神經(jīng)網(wǎng)絡；matlab

The faults diagnosis of asynchronous motorsbased on BP neural network
Abstract: With the rapid development of the economy in our country , electrification is used more and more widely, asynchronous motors have been widely applied in industrial production in various fields because of its economy, high efficiency . If the motors failure, it will cause a great loss to the production activity and people's life, so the fault diagnosis of motor has the important significance in reality.
Firstly, the classification, the application and prospects of the neural network is introduced, and the structure of asynchronous motor, the basic working principle, the fault classification and diagnosis of the motor is proposed. Aimed at the faults of three-phase asynchronous motors like a ground fault, Introduces one method of fault diagnosis based on BP neural network, then takes advantage of FFT analysis, the frequency information of vibration which is achieved from the experiment is used as the training sample of neural network. Then using these characteristic parameters as the inputs of the neura1 network，through studying and training, recognizes the type of fault.
Through the MATLAB and the principle of the BP neural network, the fault diagnosis based on BP network architecture is proposed,.By selecting enough fault samples to train neural network, the diagnosis of motor is realized. The fault type of the BP neural network established in this paper can accurately and efficiently diagnose motor, as well as is a kind of e..