基于小波理論和循環(huán)統(tǒng)計量分析的滾動軸承故障診斷
本文選題:循環(huán)統(tǒng)計量 + 小波理論; 參考:《遼寧工程技術(shù)大學(xué)》2012年碩士論文
【摘要】:滾動軸承是旋轉(zhuǎn)設(shè)備中最為常用且關(guān)鍵的器件,其能否正常工作直接影響整個機械設(shè)備,甚至生產(chǎn)線的運行狀態(tài)和職工的安全等等。因此,研究軸承的診斷技術(shù),有利于避免事故的發(fā)生以及維修體制的變革,具有非常重要的理論價值和實際意義。 由滾動軸承自身結(jié)構(gòu)的對稱性,以及旋轉(zhuǎn)(往復(fù))的運行方式,使得當(dāng)其發(fā)生損傷時引起的沖擊調(diào)制現(xiàn)象,導(dǎo)致振動信號呈現(xiàn)循環(huán)平穩(wěn)的特性,從而本文深入地研究了基于循環(huán)統(tǒng)計量分析的滾動軸承的振動信號的特征提取的方法。主要內(nèi)容有: 1)詳細討論了循環(huán)統(tǒng)計量理論,以及它們地解調(diào)性能。通過對Hilbert變換包絡(luò)解調(diào)和CAF解調(diào)性能的比較,得出CAF對于滾動軸承振動信號具有更好的分析效果,并且通過計算循環(huán)頻率等于故障特征頻率時的CAF,簡化計算,然后對其取模、FFT變換能夠提取特征信息。 2)旋轉(zhuǎn)機械的早期損傷會引起非常微弱的沖擊調(diào)制,往往淹沒在強大噪聲信息當(dāng)中,應(yīng)用小波理論來對早期微弱信息進行強化,也就是強化早期信號的微弱的循環(huán)平穩(wěn)的特性,也為繼續(xù)對信號做循環(huán)譜分析做好充足準備。 3)最后,通過多個試驗研究,,對軸承不同類型的故障,分別做了功率譜、包絡(luò)譜和循環(huán)譜分析,對比分析結(jié)果,驗證理論研究成果地正確性及有效性。
[Abstract]:Rolling bearing is the most commonly used and key device in rotating equipment. Whether it can work properly or not will directly affect the operation state of the whole mechanical equipment and even the safety of the workers and staff. Therefore, it is of great theoretical value and practical significance to study the diagnosis technology of bearing, which is helpful to avoid the accident and the change of maintenance system. Due to the symmetry of the rolling bearing's own structure and the rotating (reciprocating) operation mode, the shock modulation phenomenon caused by the damage caused by the rolling bearing causes the vibration signal to take on the characteristic of steady cycle. Therefore, the method of feature extraction of rolling bearing vibration signal based on cyclic statistical analysis is studied in this paper. The main contents are as follows: 1) the theory of cyclic statistics and their demodulation performance are discussed in detail. By comparing the performance of Hilbert transform envelope demodulation and caf demodulation, it is concluded that caf has better analysis effect for rolling bearing vibration signal, and the calculation is simplified by calculating the CAF when the cycle frequency is equal to the fault characteristic frequency. Then the FFT transform can extract the characteristic information. 2) the early damage of rotating machinery will cause very weak impulse modulation, which is often submerged in the information of strong noise. The wavelet theory is used to strengthen the weak information in the early stage, that is, to strengthen the weak cyclic stationary characteristic of the early signal, and to make sufficient preparations for the continued cyclic spectrum analysis of the signal. 3) finally, through several experiments, The power spectrum, envelope spectrum and cyclic spectrum are analyzed respectively for different types of faults of bearing. The results are compared to verify the correctness and validity of the theoretical research results.
【學(xué)位授予單位】:遼寧工程技術(shù)大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2012
【分類號】:TH165.3;TN911.7
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