本文選題：圓柱滾子軸承 + 故障診斷��； 參考：《河南科技大學(xué)》2017年碩士論文

【摘要】：圓柱滾子軸承多用于高速、重載場合,當軸承出現(xiàn)剝落、裂紋等局部故障時,故障部位將引起較大的瞬時沖擊,嚴重影響主機運行的穩(wěn)定性和生產(chǎn)安全。因此,及時識別軸承的早期故障對保障機械系統(tǒng)的安全運行、避免重大事故的發(fā)生具有重要意義。目前針對滾動軸承故障診斷技術(shù)的研究主要集中于球軸承,而對圓柱滾子軸承早期故障診斷的研究較少,且多集中于故障分析模型的建立和故障特征仿真分析。圓柱滾子軸承由于其結(jié)構(gòu)及工況特點使得其早期故障振動信號為準周期信號,且一個周期內(nèi)振動脈沖較少,振動信號信噪比較低。相對于球類軸承,圓柱滾子軸承為線接觸,對缺陷的敏感度較低,造成在相同故障尺寸下圓柱滾子軸承比球軸承更難檢測。本文針對圓柱滾子軸承故障診斷提出了兩種故障診斷方法:一種是基于希爾伯特振動分解(hilbert vibration decomposition,HVD)降噪、多頻段局部最優(yōu)頻帶疊加的滾動軸承故障診斷方法;另一種是基于峭度曲線和頻譜疊加的滾動軸承故障檢測方法。本文主要研究內(nèi)容及結(jié)論如下:1、針對軸承出現(xiàn)故障時在頻域內(nèi)出現(xiàn)多個共振峰的特點,將軸承振動信號進行頻段劃分,提取多個局部最優(yōu)頻帶,并將其頻譜進行疊加,形成基于HVD降噪和多頻段頻譜疊加的圓柱滾子軸承故障診斷方法。針對快速峭度圖頻帶劃分方法的不足,提出一種基于峭度曲線的頻帶提取方法,并通過頻譜疊加進一步突出軸承故障特征,奠定了圓柱滾子軸承早期故障特征的理論基礎(chǔ)。2、對圓柱滾子軸承進行了振動試驗,首先通過在圓柱滾子軸承不同零件上加工3mm凹坑來模擬含有較大故障的軸承,通過對含有不同故障的軸承進行振動分析,提取了不同故障類型的故障特征。隨后在圓柱滾子軸承不同零件上加工0.4mm凹坑來模擬軸承的早期故障,利用本文提出的故障診斷方法對含有早期故障軸承的振動信號進行處理,提取了圓柱滾子軸承的故障特征,并與快速峭度圖算法進行了對比,驗證了本文故障診斷方法的優(yōu)越性。3、完成了圓柱滾子軸承故障判斷系統(tǒng)的搭建,根據(jù)圓柱滾子軸承故障特征完成圓柱滾子軸承故障類型的自動判斷。
[Abstract]:Cylindrical roller bearings are often used in high speed and heavy load situations. When the bearing occurs local faults such as spalling and cracking the fault site will cause a large instantaneous impact which seriously affects the stability of the main engine and the safety of production. Therefore, it is of great significance to identify the early faults of bearing in time to ensure the safe operation of mechanical system and to avoid the occurrence of major accidents. At present, the research on fault diagnosis of rolling bearing is mainly focused on ball bearing, but the research on early fault diagnosis of cylindrical roller bearing is less, and mostly on the establishment of fault analysis model and simulation analysis of fault characteristics. Due to its structure and working conditions, the cylindrical roller bearing has its early fault vibration signal quasi periodic signal, and the vibration pulse is less and the signal-to-noise ratio of the vibration signal is lower in one period. Compared with ball bearings, cylindrical roller bearings are in linear contact, and are less sensitive to defects, resulting in more difficult detection of cylindrical roller bearings than ball bearings in the same fault size. In this paper, two fault diagnosis methods for cylindrical roller bearing are proposed: one is based on Hilbert vibration decompositionHVD (Hilbert vibration decompositionHVD) for noise reduction and multi-frequency band local optimal frequency band superposition method for rolling bearing fault diagnosis; The other is the rolling bearing fault detection method based on kurtosis curve and spectrum superposition. The main contents and conclusions of this paper are as follows: 1. Aiming at the characteristic of multiple resonance peaks in frequency domain when bearing failure occurs, the bearing vibration signal is divided into frequency bands, several local optimal frequency bands are extracted, and its frequency spectrum is superposed. A fault diagnosis method for cylindrical roller bearing based on HVD noise reduction and multi-frequency spectrum superposition is developed. Aiming at the shortage of fast kurtosis chart frequency band partition method, a frequency band extraction method based on kurtosis curve is proposed, and the bearing fault feature is further highlighted by spectrum superposition. The theoretical foundation of the early fault characteristics of cylindrical roller bearing is established. The vibration test of cylindrical roller bearing is carried out. Firstly, the bearing with larger fault is simulated by machining 3mm pits on different parts of cylindrical roller bearing. Through vibration analysis of bearing with different faults, fault characteristics of different fault types are extracted. Then 0.4mm pits are processed on different parts of cylindrical roller bearing to simulate the early fault of bearing. The vibration signal of bearing with early fault is processed by using the fault diagnosis method proposed in this paper, and the fault characteristics of cylindrical roller bearing are extracted. Compared with the fast kurtosis graph algorithm, the superiority of the fault diagnosis method in this paper is verified, and the fault judgement system of cylindrical roller bearing is built. According to the fault characteristics of cylindrical roller bearing, the fault type of cylindrical roller bearing is automatically judged.
【學(xué)位授予單位】：河南科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TH133.33

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