本文選題：齒輪箱故障診斷 + LCD��； 參考：《東北石油大學(xué)》2017年碩士論文

【摘要】：齒輪由于擁有穩(wěn)定的傳動比、大的傳動扭矩和緊湊的結(jié)構(gòu)等優(yōu)點,在改變設(shè)備轉(zhuǎn)速以及傳遞動力發(fā)面起著必不可少的作用,被廣泛的應(yīng)用于社會各領(lǐng)域的現(xiàn)代化機械設(shè)備中。雖然齒輪在機械設(shè)備的組成中無法代替,但故障發(fā)生率也非常的高,其運行狀態(tài)會嚴(yán)重影響整機的工作性能。因此,對齒輪箱進行故障診斷具有重要意義。論文的主要內(nèi)容如下:(1)介紹齒輪箱故障診斷的基本方法,研究了齒輪箱的故障類型、振動機理、信號特征。對局部特征尺度分解方法(Local characteristic-scale decomposition,簡稱LCD)及其他三種時頻分解方法的均值曲線優(yōu)劣、分解效果進行仿真分析。(2)建立齒輪箱故障實驗方案,分別測取在不同轉(zhuǎn)速下正常齒輪箱以及三種典型齒輪箱故障數(shù)據(jù),包括斷齒、裂紋及磨損故障數(shù)據(jù)。對實驗數(shù)據(jù)進行時域、頻域分析,發(fā)現(xiàn)單純的時域、頻域分析不能有效的識別齒輪箱故障特征。(3)齒輪箱振動信號具有調(diào)頻調(diào)幅的特點,故障診斷的關(guān)鍵是對齒輪箱振動調(diào)制信號進行解調(diào),從而提取出齒輪箱故障特征。此外,實際工況下的齒輪箱信號還包含了大量噪聲信號。針對此情況,本文提出了基于LCD和譜峭度的共振解調(diào)方法,對齒輪箱進行故障診斷。該方法采用LCD將信號分解為一系列調(diào)幅調(diào)頻的單分量信號,通過計算各分量和原信號的相關(guān)系數(shù)和相對熵選取合適的分量進行信號重構(gòu),再計算出重構(gòu)信號的譜峭度,根據(jù)譜峭度最大原則選出用于提取故障性沖擊成分的帶通濾波器的最佳參數(shù),最后對濾波后的信號進行共振解調(diào)分析。通過對齒輪箱仿真信號和實驗信號的分析結(jié)果表明,該方法能有效的提取出齒輪箱故障特征。(4)實際工況下齒輪箱振動信號的調(diào)制邊頻帶往往交叉在一起,形成非對稱邊帶結(jié)構(gòu),一般的頻域分析方法很難識別出來。針對此情況,將局部特征尺度分解方法和倒頻譜方法相結(jié)合應(yīng)用于齒輪箱故障診斷。首先利用LCD方法對信號進行分解,再采用倒頻譜方法對單分量信號進行分析。通過對齒輪箱仿真信號和實驗信號的分析結(jié)果表明,該方法能提取出齒輪箱故障特征,但是分析效果會受到故障程度的影響。
[Abstract]:Because of the advantages of stable transmission ratio, large transmission torque and compact structure, gear plays an essential role in changing the speed of equipment and transmitting power. It is widely used in modern machinery and equipment in various fields of society. Although the gear can not be replaced in the composition of mechanical equipment, but the rate of failure is also very high, its running state will seriously affect the performance of the whole machine. Therefore, the gearbox fault diagnosis is of great significance. The main contents of this paper are as follows: (1) the basic method of gearbox fault diagnosis is introduced, and the fault types, vibration mechanism and signal characteristics of gearbox are studied. The local characteristic scale decomposition method (LCD) and three other time-frequency decomposition methods are simulated and analyzed to establish the gearbox fault test scheme. The fault data of normal gearbox and three typical gearboxes were measured at different rotational speeds, including broken teeth, cracks and wear faults. By analyzing the experimental data in the time domain and the frequency domain, it is found that the simple time domain and frequency domain analysis can not effectively identify the gearbox fault characteristics. (3) the vibration signal of the gear box has the characteristics of frequency modulation and amplitude modulation. The key of fault diagnosis is to demodulate the vibration modulation signal of gearbox and extract the fault feature of gearbox. In addition, a large number of noise signals are also included in the gearbox signals under actual working conditions. In this paper, a method of resonance demodulation based on LCD and spectral kurtosis is proposed to diagnose the gearbox fault. In this method, the signal is decomposed into a series of single-component signals with amplitude modulation and frequency modulation by LCD. The spectral kurtosis of the reconstructed signal is calculated by calculating the correlation coefficient and relative entropy of each component and the original signal to select the appropriate components for signal reconstruction. According to the principle of maximum spectral kurtosis, the optimal parameters of the band-pass filter used to extract the fault impulse components are selected. Finally, the resonance demodulation analysis of the filtered signal is carried out. Through the analysis of the simulation signal and the experimental signal of the gearbox, the results show that the method can effectively extract the gearbox fault characteristics. 4) under the actual working conditions, the modulated frequency bands of the vibration signals of the gearbox are often crossed together to form an asymmetric sideband structure. General frequency domain analysis methods are difficult to identify. In this case, the local characteristic scale decomposition method and the cepstrum method are applied to the gearbox fault diagnosis. Firstly, the signal is decomposed by LCD method, and then the single component signal is analyzed by cepstrum method. Through the analysis of the simulation and experimental signals of the gearbox, it is shown that the method can extract the fault characteristics of the gearbox, but the effect of the analysis will be affected by the degree of the fault.
【學(xué)位授予單位】：東北石油大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TH132.41
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本文編號：1899818