本文關(guān)鍵詞： 軸承故障診斷 隨機共振 時頻分析 多尺度噪聲調(diào)節(jié) 算法軟件實現(xiàn)　出處：《中國科學(xué)技術(shù)大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：旋轉(zhuǎn)設(shè)備是工業(yè)機械中最重要的部件之一,而軸承則是一種典型的旋轉(zhuǎn)設(shè)備。如果機械系統(tǒng)中的軸承有故障,不僅會影響系統(tǒng)的正常運行,也有可能導(dǎo)致一些意想不到的危險后果,所以需要及時發(fā)現(xiàn)軸承的早期缺陷。一般通過分析振動信號來進行軸承的狀態(tài)檢測和故障診斷,但是受到工作環(huán)境的噪聲及軸承與其他機械零件耦合而產(chǎn)生的噪聲的影響,故障診斷的難度很大。因此,亟需找到一種有效的微弱信號檢測的方法。在微弱信號檢測中,隨機共振是一種利用噪聲來增強周期性信號的有效方法�？紤]到有故障的軸承振動信號的非平穩(wěn)特性,本文研究了時頻分布中的隨機共振。本文提出了一種稱為多尺度隨機共振譜的新方法,以提高檢測初始缺陷信號的有效性。該方法的理論依據(jù)在于(1)故障導(dǎo)致的瞬變主要位于時頻分布中的特定頻帶,因此只有該頻段的噪聲才能激活隨機共振效應(yīng);(2)時頻分布上的每一個頻率上對應(yīng)于在特定頻率上調(diào)制的包絡(luò),因此在時頻分布中存在用于每個頻率標度的調(diào)制系統(tǒng)。本文提出的新方法將時頻分布的每個尺度視為特定頻率的調(diào)制系統(tǒng),由于有用信息僅包含在測量信號的特定尺度中,不同調(diào)制系統(tǒng)中的噪聲在用隨機共振技術(shù)增強缺陷信息方面將具有不同的有效性。在對實驗數(shù)據(jù)的分析中,相比起各種經(jīng)典的隨機共振方法,本文所提出的方法在識別滾動軸承的故障頻率方面具有更多的優(yōu)勢,同時也顯示了在診斷混合故障的振動信號中的潛力。此外,本文還探索了兩種機械故障診斷算法的軟件實現(xiàn),其一是在智能手機中應(yīng)用故障診斷算法,其二是將算法部署到服務(wù)器上并通過網(wǎng)絡(luò)瀏覽器將診斷結(jié)果可視化,這兩種方法分別實現(xiàn)了在線與離線的故障診斷。
[Abstract]:Rotating equipment is one of the most important components in industrial machinery, while the bearing is a kind of typical rotating equipment. If the bearings in the mechanical system fault, will not only affect the normal operation of the system, may also lead to some unexpected and dangerous consequences, so they need to find out the early defect of bearing. By analysis of vibration signal to carry out detection and fault diagnosis of the bearing condition, but by the impact of noise and noise of bearing working environment and other mechanical parts generated by a combination of the fault diagnosis is very difficult. Therefore, it is urgent to find an effective method of weak signal detection. In weak signal detection, stochastic resonance is a kind of effective enhancement the method of periodic signal with noise. Considering the non-stationary characteristics of vibration signals of bearing fault, this paper studies the time-frequency distribution of stochastic resonance is proposed in this paper. A new method called random resonance spectra of multi-scale, in order to improve the effectiveness of the detection of initial defect signal. The theoretical basis of this method is that (1) caused by the fault transient mainly in the specific frequency band in frequency distribution, so the band noise can only activate the stochastic resonance effect; (2) when the envelope of each frequency distribution on the frequency corresponding to the modulation at a particular frequency, so the time-frequency distribution in frequency modulation system for each scale. A new method is put forward in this paper at each scale frequency distribution as a particular frequency modulation system, the useful information contained in a specific scale the measurement signal in the noise of different modulation system in the enhanced defect information will have different effective use of stochastic resonance technology. In the analysis of the experimental data, compared with the classical method of stochastic resonance, the Has the advantage of fault frequency method of rolling bearing in the recognition, but also shows the vibration signal in fault diagnosis of mixed potential. In addition, this paper also explores the two kinds of mechanical fault diagnosis algorithm of the software, it is should be used in the fault diagnosis algorithm of intelligent mobile phone, the second is the algorithm deployed to the server through a web browser and the diagnostic results visualization, these two methods are used to implement the fault diagnosis online and offline.

【學(xué)位授予單位】：中國科學(xué)技術(shù)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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本文編號：1449070