本文選題：滾動軸承 + 故障診斷��； 參考：《安徽工業(yè)大學(xué)》2017年碩士論文

【摘要】：電機是一種極重要的旋轉(zhuǎn)機械。滾動軸承是電機設(shè)備中最常用的零部件之一,也是易損件之一。滾動軸承一旦發(fā)生故障,不僅會影響電機本身的運行,還會引起連鎖反應(yīng),造成嚴(yán)重安全事故。為了保證電機的安全運行,防止生產(chǎn)事故的發(fā)生,有必要對在線式滾動軸承故障診斷系統(tǒng)進行研究。本文首先對滾動軸承的典型結(jié)構(gòu)、故障表現(xiàn)形式以及故障機理進行了研究,并介紹了軸承故障診斷的常用方法,通過對比它們的優(yōu)缺點,最終選擇了振動信號分析法作為軸承故障診斷方法,它能夠迅速、全面地提取軸承的故障特征信息,從而為軸承故障診斷系統(tǒng)的開發(fā)提供了理論基礎(chǔ)。其次,對基于振動信號的故障診斷方法做了詳細的介紹,包括時域分析法、頻域分析法、希爾伯特解調(diào)法、小波分析以及經(jīng)驗?zāi)B(tài)分解法。本文針對傳統(tǒng)的經(jīng)驗?zāi)B(tài)分解法存在的模態(tài)混疊、包含虛假分量等問題,提出了一種改進的經(jīng)驗?zāi)B(tài)分解法,并將傳統(tǒng)的故障診斷方法與改進經(jīng)驗?zāi)B(tài)分解相結(jié)合,提出了軸承故障綜合診斷方法,該方法可以有效地提高故障診斷的效率和準(zhǔn)確性。本文利用LabVIEW軟件開發(fā)平臺對滾動軸承故障診斷系統(tǒng)進行了總體設(shè)計。硬件方面主要包括傳感器的選型、信號調(diào)理電路與數(shù)據(jù)采集裝置的設(shè)計。軟件方面主要實現(xiàn)了基于LabVIEW與MATLAB混合編程的故障診斷系統(tǒng)各功能模塊。最后,通過搭建的實驗平臺對滾動軸承故障診斷系統(tǒng)的實用性進行了驗證。實驗結(jié)果與預(yù)期一致,表明本文設(shè)計的軸承故障診斷系統(tǒng)能夠有效診斷出軸承故障,具有一定的實用價值。
[Abstract]:Motor is a very important rotating machine. Rolling bearing is one of the most commonly used parts and components in motor equipment. Once the rolling bearing breaks down, it will not only affect the operation of the motor itself, but also cause chain reaction and cause serious safety accident. In order to ensure the safe operation of the motor and prevent the production accident, it is necessary to study the on-line rolling bearing fault diagnosis system. In this paper, the typical structure, fault representation and fault mechanism of rolling bearing are studied, and the common methods of bearing fault diagnosis are introduced, and their advantages and disadvantages are compared. Finally, the vibration signal analysis method is chosen as the bearing fault diagnosis method, which can extract the bearing fault characteristic information quickly and comprehensively, thus providing the theoretical basis for the development of the bearing fault diagnosis system. Secondly, the fault diagnosis method based on vibration signal is introduced in detail, including time domain analysis, frequency domain analysis, Hilbert demodulation, wavelet analysis and empirical mode decomposition. In this paper, an improved empirical mode decomposition method is proposed to solve the problems of modal aliasing and false component in the traditional empirical mode decomposition method, which combines the traditional fault diagnosis method with the improved empirical mode decomposition method. A comprehensive diagnosis method for bearing faults is proposed, which can effectively improve the efficiency and accuracy of fault diagnosis. In this paper, the overall design of rolling bearing fault diagnosis system is carried out by using LabVIEW software development platform. Hardware mainly includes sensor selection, signal conditioning circuit and data acquisition device design. In the aspect of software, the function modules of fault diagnosis system based on LabVIEW and MATLAB are realized. Finally, the practicability of the rolling bearing fault diagnosis system is verified by the experimental platform. The experimental results are in agreement with the expectation, which indicates that the bearing fault diagnosis system designed in this paper can diagnose bearing fault effectively and has certain practical value.
【學(xué)位授予單位】：安徽工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TM307

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