發(fā)布時(shí)間：2018-01-06 23:35

  本文關(guān)鍵詞：基于支持向量機(jī)的數(shù)控機(jī)床進(jìn)給系統(tǒng)滾動(dòng)軸承故障診斷研究　出處：《青島理工大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 數(shù)控機(jī)床 滾動(dòng)軸承 故障診斷 小波包分解 能量特征量 支持向量機(jī)

【摘要】：近年來(lái),我國(guó)大力發(fā)展裝備制造業(yè),對(duì)數(shù)控設(shè)備關(guān)鍵部件的研發(fā)、生產(chǎn)、制造以及故障診斷方面加大了研究。為了滿足目前生產(chǎn)中對(duì)加工質(zhì)量和精度更高的要求,實(shí)現(xiàn)裝備制造業(yè)的全面發(fā)展,國(guó)家已將數(shù)控設(shè)備研發(fā)列入十一五重大科技專項(xiàng)。數(shù)控機(jī)床加工中,旋轉(zhuǎn)部件的工作狀態(tài)是保證加工質(zhì)量的的關(guān)鍵因素,數(shù)控機(jī)床在裝備制造業(yè)中占據(jù)著重要的地位,滾動(dòng)軸承是數(shù)控機(jī)床中十分關(guān)鍵的部件,當(dāng)機(jī)床中軸承發(fā)生故障時(shí),不可避免的對(duì)機(jī)床產(chǎn)生影響,有數(shù)據(jù)顯示,目前數(shù)控設(shè)備中30%的故障是由于軸承故障引起的,軸承一旦發(fā)生故障會(huì)嚴(yán)重影響生產(chǎn)效率,且狀況嚴(yán)重時(shí)造成重大安全事故,因此,開(kāi)展對(duì)數(shù)控機(jī)床滾動(dòng)軸承的故障在線診斷,監(jiān)測(cè)機(jī)床軸承的運(yùn)行狀態(tài),具有重要的實(shí)用意義和經(jīng)濟(jì)意義。 本文分析了數(shù)控機(jī)床進(jìn)給系統(tǒng)中軸承部件的常用種類,以及滾動(dòng)軸承的主要結(jié)構(gòu),在此基礎(chǔ)上確定研究對(duì)象為角接觸球軸承,分析了軸承的主要故障形式和形成機(jī)理以及故障振動(dòng)頻率,提出了基于振動(dòng)信號(hào)和支持向量機(jī)的軸承故障診斷方法,研究了振動(dòng)信號(hào)的小波包分析方法,將檢測(cè)振動(dòng)信號(hào)進(jìn)行小波包分解,得到小波包能量作為特征向量,最后通過(guò)實(shí)驗(yàn)分析對(duì)該方法進(jìn)行了實(shí)驗(yàn)驗(yàn)證。 首先,從滾動(dòng)軸承的主要種類、結(jié)構(gòu)特點(diǎn)入手,在此基礎(chǔ)上著重分析了數(shù)控機(jī)床進(jìn)給系統(tǒng)滾動(dòng)軸承的主要失效形式以及各失效形式產(chǎn)生的原因和現(xiàn)象,對(duì)失效形式、原因、現(xiàn)象進(jìn)行了歸納總結(jié)；當(dāng)機(jī)床進(jìn)給軸承發(fā)生故障時(shí),會(huì)對(duì)數(shù)控機(jī)床產(chǎn)生影響,本文分析了滾動(dòng)軸承常見(jiàn)故障對(duì)數(shù)控機(jī)床進(jìn)給系統(tǒng)的影響；對(duì)滾動(dòng)軸承振動(dòng)信號(hào)的特性進(jìn)行了深入詳細(xì)的研究。 其次,研究了滾動(dòng)軸承故障診斷軟硬件系統(tǒng)的設(shè)計(jì),基于LabVIEW和MATLAB軟件實(shí)現(xiàn)故障信號(hào)的數(shù)據(jù)采集和數(shù)據(jù)分析處理,數(shù)據(jù)分析主要實(shí)現(xiàn)了振動(dòng)信號(hào)的小波包分解以及小波包能量的計(jì)算,然后利用MATLAB支持向量機(jī)工具箱建立支持向量機(jī)模型,實(shí)現(xiàn)滾動(dòng)軸承故障的模式識(shí)別。 再次,在西門子數(shù)控機(jī)床802Dsl上搭建實(shí)驗(yàn)臺(tái),對(duì)進(jìn)給系統(tǒng)滾動(dòng)軸承的故障進(jìn)行了實(shí)驗(yàn)分析,驗(yàn)證了本文基于支持向量機(jī)的數(shù)控機(jī)床滾動(dòng)軸承故障診斷的有效性。 最后,研究了基于PXI-6281多功能數(shù)據(jù)采集卡的滾動(dòng)軸承振動(dòng)信號(hào)的數(shù)據(jù)采集技術(shù)及基于Microsoft Access數(shù)據(jù)庫(kù)的數(shù)據(jù)管理技術(shù)與方法,以LabVIEW為平臺(tái),開(kāi)發(fā)了由數(shù)據(jù)采集模塊、數(shù)據(jù)處理模塊和數(shù)據(jù)分析模塊組成的數(shù)控機(jī)床進(jìn)給系統(tǒng)滾動(dòng)軸承故障診斷系統(tǒng)。
[Abstract]:In recent years, our country vigorously develops the equipment manufacturing industry, to the numerical control equipment key component research and development, the production. In order to meet the requirement of higher machining quality and precision in current production, the equipment manufacturing industry can be developed in an all-round way. The research and development of numerical control equipment has been listed as a major scientific and technological project in the 11th Five-Year Plan. The working state of rotating parts is the key factor to ensure the quality of machining in NC machine tool processing. The CNC machine tool occupies an important position in the equipment manufacturing industry. The rolling bearing is a very important part in the NC machine tool. When the bearing in the machine tool breaks down, it will inevitably have an impact on the machine tool. At present, the fault of 30% in the NC equipment is caused by the bearing fault, once the bearing failure will seriously affect the production efficiency, and when the situation is serious, there will be a serious safety accident. It is of great practical and economic significance to carry out on-line fault diagnosis of rolling bearings of NC machine tools and monitor the running state of machine tools bearings. This paper analyzes the common types of bearing parts in the feed system of CNC machine tools and the main structure of rolling bearings. On this basis, the object of study is angular contact ball bearings. The main fault form and forming mechanism of bearing and the frequency of fault vibration are analyzed. The method of bearing fault diagnosis based on vibration signal and support vector machine is put forward, and the wavelet packet analysis method of vibration signal is studied. The wavelet packet energy is obtained as the eigenvector by wavelet packet decomposition of the detected vibration signal. Finally, the method is verified by experimental analysis. First of all, starting with the main types and structural characteristics of rolling bearings, the main failure forms of rolling bearings in CNC machine tool feed system and the causes and phenomena of each failure forms are analyzed emphatically. The form, cause and phenomenon of failure are summarized. When the feed bearing of the machine tool breaks down, it will affect the NC machine tool. This paper analyzes the influence of the common fault of the rolling bearing on the feed system of the NC machine tool. The characteristics of rolling bearing vibration signal are studied in detail. Secondly, the software and hardware design of rolling bearing fault diagnosis system is studied. The data acquisition and data analysis of fault signals are realized based on LabVIEW and MATLAB software. The data analysis mainly realizes the wavelet packet decomposition of vibration signal and the calculation of wavelet packet energy. Then the support vector machine model is established by using MATLAB support vector machine toolbox. The pattern recognition of rolling bearing fault is realized. Thirdly, the experiment platform is built on 802DSL of Siemens NC machine tool, and the fault of rolling bearing of feed system is analyzed experimentally. The effectiveness of bearing fault diagnosis of NC machine tool based on support vector machine is verified. Finally. The data acquisition technology of rolling bearing vibration signal based on PXI-6281 multi-function data acquisition card and the data management technology and method based on Microsoft Access database are studied. Based on LabVIEW, a rolling bearing fault diagnosis system of NC machine tool feed system is developed, which is composed of data acquisition module, data processing module and data analysis module.
【學(xué)位授予單位】：青島理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：TG659;TH165.3

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 徐振輝,馬立元;滾動(dòng)軸承的故障特征提取[J];兵工自動(dòng)化;2004年01期

2 陳佳;傅攀;;基于小波包和概率神經(jīng)網(wǎng)絡(luò)的滾動(dòng)軸承故障診斷[J];四川兵工學(xué)報(bào);2011年05期

3 周俊麗;周久華;;滾動(dòng)軸承故障機(jī)理與診斷策略[J];四川兵工學(xué)報(bào);2012年04期

4 劉崇春,裘正定;一種基于Morlet小波的振動(dòng)信號(hào)包絡(luò)提取方法[J];電路與系統(tǒng)學(xué)報(bào);2000年01期

5 趙志宏;楊紹普;;基于相對(duì)小波能量的滾動(dòng)軸承故障診斷[J];電子測(cè)量與儀器學(xué)報(bào);2011年01期

6 陳會(huì)蓮;馬文麗;張莉;;神經(jīng)網(wǎng)絡(luò)專家系統(tǒng)在發(fā)動(dòng)機(jī)故障診斷中的應(yīng)用[J];中國(guó)農(nóng)機(jī)化;2012年05期

7 陳季云;李娟;;基于小波包-支持向量機(jī)的滾動(dòng)軸承故障診斷[J];化工自動(dòng)化及儀表;2010年09期

8 趙明元,朱衡君;機(jī)車軸承故障診斷與預(yù)測(cè)系統(tǒng)[J];機(jī)車電傳動(dòng);2005年05期

9 羅兵;王憲洲;宋萬(wàn)成;;基于參數(shù)辨識(shí)模型的彈道擬合方法仿真研究[J];艦船電子工程;2012年01期

10 周曉宏;數(shù)控機(jī)床進(jìn)給伺服系統(tǒng)的常見(jiàn)故障及診斷[J];機(jī)電一體化;2003年03期

，

本文編號(hào)：1390036