【摘要】：滾動軸承是旋轉(zhuǎn)機(jī)械的重要零部件之一,其工作狀態(tài)直接決定機(jī)械系統(tǒng)的性能及運(yùn)行工況。在實(shí)際的工程實(shí)踐中,滾動軸承的一個微小故障輕則可能導(dǎo)致生產(chǎn)線的停機(jī),重則還可能損壞設(shè)備并造成嚴(yán)重的經(jīng)濟(jì)損失。因此,開展?jié)L動軸承故障診斷與預(yù)報(bào)的研究對避免重大事故、變革維修體制和促進(jìn)經(jīng)濟(jì)發(fā)展等都具有重要的現(xiàn)實(shí)意義。 本文介紹了滾動軸承的機(jī)械結(jié)構(gòu)、振動機(jī)理、故障形式及成因和故障特征等。詳細(xì)研究了故障診斷領(lǐng)域應(yīng)用較多的理論和方法,這些方法包括特征參數(shù)判別診斷法、共振解調(diào)診斷法、基于Hilbert-Huang變換的診斷法。本文利用振動法采集滾動軸承的故障信號,并搭建了現(xiàn)場試驗(yàn)臺進(jìn)行信號采集。 通過對共振解調(diào)技術(shù)和Hilbert-Huang變換的研究發(fā)現(xiàn):基于傳統(tǒng)的共振解調(diào)技術(shù)的診斷方法存在帶通濾波參數(shù)(中心頻率和濾波帶寬)需要預(yù)先確定和固定的濾波頻帶具有局限性等缺陷,而基于Hilbert-Huang變換的診斷方法雖然能夠同時從時間尺度和頻率尺度很好的描述信號的變化情況,但是通過Hilbert譜和邊際譜還是難以觀察到明顯的故障特征信號。本文采用將這兩種診斷方法結(jié)合起來進(jìn)行故障診斷,利用了EMD分解的自適應(yīng)性彌補(bǔ)了共振解調(diào)技術(shù)需要固定濾波參數(shù)的缺陷,利用共振解調(diào)技術(shù)能提取調(diào)制在高頻固有振動中故障信息的能力彌補(bǔ)了HHT無法突顯故障特征的缺陷,并用實(shí)驗(yàn)驗(yàn)證了該方法的有效性,實(shí)驗(yàn)結(jié)果表明基于EMD的共振解調(diào)技術(shù)能夠準(zhǔn)確可靠的進(jìn)行滾動軸承的故障診斷。并在此基礎(chǔ)上,針對EMD共振解調(diào)故障診斷方法存在計(jì)算量大和選取IMF分量進(jìn)行特征提取需要人工干預(yù)的缺陷,本文提出了改進(jìn)的EMD共振解調(diào)故障診斷方法,并將該改進(jìn)方法與傳統(tǒng)的共振解調(diào)方法和EMD共振解調(diào)方法在計(jì)算量、智能程度和有效性方面進(jìn)行了對比分析,分析結(jié)果表明本文提出的改進(jìn)EMD共振解調(diào)方法優(yōu)于傳統(tǒng)的共振解調(diào)法和EMD共振解調(diào)方法。
[Abstract]:Rolling bearing is one of the important parts of rotating machinery. Its working state directly determines the performance and operating condition of the mechanical system. In practical engineering practice, a slight failure of rolling bearing may lead to the shutdown of the production line, and may also damage the equipment and cause serious economic losses. Therefore, the research on fault diagnosis and prediction of rolling bearings is of great practical significance for avoiding major accidents, reforming maintenance system and promoting economic development. In this paper, the mechanical structure, vibration mechanism, fault form, cause of failure and fault characteristics of rolling bearing are introduced. The theories and methods applied in the field of fault diagnosis are studied in detail. These methods include characteristic parameter discriminant diagnosis method, resonance demodulation diagnosis method and diagnosis method based on Hilbert-Huang transform. In this paper, the vibration method is used to collect the fault signal of rolling bearing, and the field test-bed is built to collect the signal. Through the research of resonance demodulation technology and Hilbert-Huang transform, it is found that the diagnosis method based on traditional resonance demodulation technology has bandpass filter parameters (center frequency and filter bandwidth) which need to be determined and fixed in advance. With limitations and other defects, The diagnosis method based on Hilbert-Huang transform can describe the change of signal from both time scale and frequency scale at the same time, but it is difficult to observe the obvious fault characteristic signal by Hilbert spectrum and marginal spectrum. In this paper, the two diagnostic methods are combined for fault diagnosis, and the self-adaptability of EMD decomposition is used to make up for the defect that resonance demodulation technology needs fixed filter parameters. The fault information of modulation in high frequency natural vibration can be extracted by resonance demodulation technology, which makes up for the defect that HHT can not highlight the fault characteristics, and the effectiveness of this method is verified by experiments. The experimental results show that the resonance demodulation technology based on EMD can accurately and reliably diagnose the fault of rolling bearings. On this basis, in view of the shortcomings of EMD resonance demodulation fault diagnosis method, such as large computational complexity and the need of manual intervention to select IMF components for feature extraction, an improved EMD resonance demodulation fault diagnosis method is proposed in this paper. The improved method is compared with the traditional resonance demodulation method and the EMD resonance demodulation method in terms of computation, intelligence and effectiveness. The analysis results show that the improved EMD resonance demodulation method is superior to the traditional resonance demodulation method and the EMD resonance demodulation method.
【學(xué)位授予單位】：上海師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2011
【分類號】：TH133.33;TH165.3

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本文編號：2462389