【摘要】：旋轉機械廣泛應用于機械、冶金、電力、化工等行業(yè)。如果旋轉機械發(fā)生故障而未及時控制和消除，則可能導致設備損壞，不僅造成巨大的經濟損失，甚至會危及人身安全，，后果極為嚴重，因此對于旋轉機械的故障診斷具有重要的意義。由于轉子的軸心軌跡可以反映轉子故障類型，本課題從軸心軌跡入手研究轉子故障的自動診斷方法。具體內容包括： (1)軸心軌跡提純：利用小波方法對軸心軌跡進行提純。首先對比了選用不同的小波函數以及分解到不同的層數時提純效果的差別，并選取出最佳的小波基和分解層數；然后根據轉子振動信號的特點，分析了采樣頻率和轉速對提純效果的影響，并采用對信號重采樣的方法降低這種影響，保證提純效果； (2)軸心軌跡特征提�。涸谳S心軌跡提純時重采樣的基礎上進行下采樣，計算軸心軌跡在各個旋轉周期內的極徑（軸心軌跡上各點到基點O的距離）并對其進行平移、伸縮、旋轉歸一化，采用歸一化的極徑序列作為軸心軌跡的特征。通過仿真試驗驗證了歸一化的極徑序列對于不同軸心軌跡具有不同的變化特征，而且下采樣后的極徑序列在每個旋轉周期有相同的樣本長度，便于下一步識別； (3)軸心軌跡的識別：采用軸心軌跡的極徑序列作為樣本，討論了建立相應的BP神經網絡的過程，并用其對樣本進行訓練和識別，結果表明該網絡能有效區(qū)分不同類型的軸心軌跡； (4)試驗驗證：在轉子-軸承試驗臺上，測得幾組實際故障的軸心軌跡，并對實測信號進行提純、特征提取和識別，結果表明本文的方法是有效的。
[Abstract]:Rotating machinery is widely used in machinery, metallurgy, power, chemical and other industries. If the failure of rotating machinery is not controlled and eliminated in time, it may lead to equipment damage, which may not only cause huge economic losses, but even endanger personal safety, and the consequences are very serious, so it is of great significance for the fault diagnosis of rotating machinery. Because the axial trajectory of rotor can reflect the type of rotor fault, the automatic diagnosis method of rotor fault is studied in this paper. The main contents are as follows: (1) Axis trajectory purification: wavelet method is used to purify the axis trajectory. Firstly, the difference of purification effect when different wavelet functions are selected and decomposed into different layers is compared, and the best wavelet basis and decomposition layer number are selected. Then, according to the characteristics of rotor vibration signal, the influence of sampling frequency and rotating speed on purification effect is analyzed, and the method of signal resampling is used to reduce this effect and ensure the purification effect. (2) feature extraction of axis trajectory: on the basis of resampling when the axis trajectory is purified, the polar diameter of the axis trajectory in each rotation cycle (the distance from each point on the axis trajectory to the base point O) is calculated, and its translation, expansion and rotation normalization are carried out. The normalized polar diameter sequence is used as the characteristics of the axis trajectory. The simulation results show that the normalized polar diameter sequence has different variation characteristics for different axis trajectories, and the undersampled polar diameter sequence has the same sample length in each rotation cycle, which is convenient for the next step identification. (3) Identification of axis trajectory: using the polar diameter sequence of axis trajectory as sample, the process of establishing corresponding BP neural network is discussed, and the samples are trained and identified. The results show that the network can effectively distinguish different types of axis trajectory. (4) the experimental results show that the axial center trajectories of several groups of actual faults are measured on the rotor-bearing test-bed, and the measured signals are purified, feature extraction and recognition are carried out. the results show that the method in this paper is effective.
【學位授予單位】：西安科技大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：TH165.3

【參考文獻】

相關期刊論文 前5條

1 史東鋒;瞬態(tài)提純軸心軌跡在回轉機械診斷中的應用研究[J];西安交通大學學報;1999年03期

2 洪小達;圖像編碼技術的發(fā)展[J];中國信息導報;1999年03期

3 韓西京,李錄平,史鐵林,楊叔子;旋轉機械軸心軌跡的自動識別[J];振動.測試與診斷;1997年03期

4 趙林度,盛昭瀚;離散余弦變換在軸心軌跡自動識別中的應用[J];振動.測試與診斷;1999年01期

5 張文斌;周曉軍;沈路;李俊生;楊先勇;林勇;;基于形態(tài)小波的轉子軸心軌跡提純[J];浙江大學學報(工學版);2010年08期

相關博士學位論文 前1條

1 秦毅;信號小波理論與一體化小波分析儀的研究[D];重慶大學;2008年

本文編號：2512003