【摘要】：在機(jī)械設(shè)備故障中因?yàn)闈L動(dòng)軸承受損而發(fā)生故障的概率非常大,滾動(dòng)軸承的工作狀況將直接影響到整個(gè)機(jī)械設(shè)備的運(yùn)轉(zhuǎn)。滾動(dòng)軸承故障的診斷方法有很多種,隨著科學(xué)技術(shù)的發(fā)展與進(jìn)步,對(duì)滾動(dòng)軸承檢測(cè)的實(shí)時(shí)性和診斷結(jié)果、維修方案的準(zhǔn)確性等提出了新的要求,這對(duì)于滾動(dòng)軸承故障診斷的研究具有非常重要的意義。 為了能夠更好的對(duì)滾動(dòng)軸承故障進(jìn)行診斷,本文分析了當(dāng)前應(yīng)用于滾動(dòng)軸承故障診斷的主要方法,應(yīng)用當(dāng)前使用較多的小波分析理論,對(duì)軸承的振動(dòng)信號(hào)進(jìn)行閾值降噪,并提出了較為合理的新閾值函數(shù),對(duì)新閾值函數(shù)進(jìn)行了理論分析,實(shí)驗(yàn)結(jié)果表明,新閾值函數(shù)對(duì)含噪信號(hào)的降噪效果,比傳統(tǒng)閾值函數(shù)的降噪效果更加優(yōu)越。同時(shí),采用小波包的方法提取軸承故障特征信息,將BP神經(jīng)網(wǎng)絡(luò)智能化診斷引入診斷系統(tǒng)中,以小波包提取的特征信息作為BP神經(jīng)網(wǎng)絡(luò)訓(xùn)練樣本和預(yù)測(cè)樣本。因BP神經(jīng)網(wǎng)絡(luò)自身存在易于陷入局部極小值和收斂速度慢等缺陷,采用遺傳算法對(duì)BP神經(jīng)網(wǎng)絡(luò)的初始權(quán)值和閾值進(jìn)行優(yōu)化。優(yōu)化的BP神經(jīng)網(wǎng)絡(luò)可以較好地克服BP網(wǎng)絡(luò)的缺陷,在滾動(dòng)軸承故障訓(xùn)練和診斷時(shí),可以找到全局最優(yōu)值。采用LabVIEW友好界面的開發(fā)功能和MATLAB強(qiáng)大的數(shù)值分析和數(shù)據(jù)處理的功能,進(jìn)行滾動(dòng)軸承故障診斷系統(tǒng)的研發(fā),充分利用LabVIEW自帶的MATLAB script節(jié)點(diǎn),將兩種軟件的優(yōu)點(diǎn)結(jié)合到一起,實(shí)現(xiàn)了滾動(dòng)軸承的智能化診斷,這也使得該系統(tǒng)對(duì)故障的診斷速度和準(zhǔn)確度得到較大的提高。
[Abstract]:The fault probability of the rolling bearing is very large in the mechanical equipment fault. The working condition of the rolling bearing will directly affect the operation of the whole machinery and equipment. There are many kinds of fault diagnosis methods for rolling bearings. With the development and progress of science and technology, new requirements are put forward for the real-time detection and diagnostic results of rolling bearings, the accuracy of maintenance schemes, etc. This is of great significance to the research of rolling bearing fault diagnosis. In order to diagnose the fault of rolling bearing better, this paper analyzes the main methods of fault diagnosis of rolling bearing at present, and applies more wavelet analysis theory to reduce the noise of the vibration signal of bearing. A reasonable new threshold function is put forward and the theoretical analysis of the new threshold function is made. The experimental results show that the new threshold function is more effective than the traditional threshold function in reducing the noise of the noisy signal. At the same time, the fault feature information of bearing is extracted by wavelet packet method, and the intelligent diagnosis of BP neural network is introduced into the diagnosis system. The feature information extracted by wavelet packet is used as the training sample and prediction sample of BP neural network. Because the BP neural network is easy to fall into the local minimum and the convergence speed is slow, the genetic algorithm is used to optimize the initial weights and thresholds of the BP neural network. The optimized BP neural network can overcome the defects of BP neural network and find the global optimal value in the fault training and diagnosis of rolling bearing. By adopting the development function of LabVIEW friendly interface and the powerful function of numerical analysis and data processing of MATLAB, the research and development of rolling bearing fault diagnosis system are carried out, and the advantages of the two kinds of software are combined by making full use of the MATLAB script node of LabVIEW. The intelligent diagnosis of rolling bearing is realized, which improves the speed and accuracy of fault diagnosis.
【學(xué)位授予單位】：山東理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：TP183;TH165.3

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本文編號(hào)：2412858