滑动轴承油膜失稳振动的二阶定向循环平稳性分析
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摘要
定义了二阶定向循环平稳统计量,提出了基于二阶定向循环平稳的信号分析方法。该方法将用于单通道实信号分析的二阶循环统计量扩展到复信号,并定义了正交双通道融合复信号的定向循环自相关、定向循环谱相关密度。为了验证该方法,利用转子试验台模拟滑动轴承旋转机械的油膜失稳故障以获取数据,分析结果表明该方法不仅能够提取系统在某一截面内的周期性振动特征,而且能够揭示转子在指定循环频率处的旋向。此外二阶定向循环谱相关密度在指定频率处的切片能显示更加丰富的转子频率耦合调制信息,试验结果验证了该方法的有效性。
The second-order directional cyclostationarity was defined based on the second-order cycle statistics. This method extended the second-order cycle statistics restricted to analyze real signals to processing complex signals obtained from journal bearings supporting a rotor system operating with oil whip by defining the directional cycle autocorrelation( DCA) and the directional cycle spectral correlation density( DCSCD). To verify this method,a rotation test bench was used to simulate rotating machinery oil whip fault. The analysis of the experimental data showed that the periodic vibration characteristics and rotation direction within the rotor system cross section of interest can be easily found; besides,the slice of DCSCD at the specified frequency can reveal richer information about rotor frequency coupling modulation,the effectiveness of the method is verified.
The second-order directional cyclostationarity was defined based on the second-order cycle statistics. This method extended the second-order cycle statistics restricted to analyze real signals to processing complex signals obtained from journal bearings supporting a rotor system operating with oil whip by defining the directional cycle autocorrelation( DCA) and the directional cycle spectral correlation density( DCSCD). To verify this method,a rotation test bench was used to simulate rotating machinery oil whip fault. The analysis of the experimental data showed that the periodic vibration characteristics and rotation direction within the rotor system cross section of interest can be easily found; besides,the slice of DCSCD at the specified frequency can reveal richer information about rotor frequency coupling modulation,the effectiveness of the method is verified.
引文
[1]周宇.基于循环平稳信号二维平面表示的滚动轴承早期故障诊断方法研究[D].上海:上海交通大学,2012.
[2]彭畅,柏林,谢小亮.基于EEMD,度量因子和快速峭度图的滚动轴承故障诊断方法[J].振动与冲击,2012,31(20):143-146.PENG Chang,BO Lin,XIE Xiao-liang.Fault diagnois method ofrolling element bearing based on EEMD,measurefactor and fast kurtogram[J].Journal of Vibration and Shock,2012,31(20):143-146.
[3]毕果.基于循环平稳的滚动轴承及齿轮微弱故障特征提取应用研究[D].上海:上海交通大学,2007.
[4]Capdessus C,Sidahmed M,Lacoume J L.Cyclostationary processes:application in gear faults early diagnosis[J].Mechanical Systems and Signal Processing,2000,14:371-385.
[5]Mccormick A C,Nandi A K.Cyclostationarity in rotating machine vibrations[J].Mechanical System and Signal Processing,1998,12(2):225-242.
[6]Randall R B,Antoni J,Chobsaard S.The relationship between spectral correlation and envelope analysis in the diagnostics of bearing faults and other cyclostationary machine signals[J].Mechanical Systems and Signal Processing,2001,15:945-962.
[7]李力,屈梁生.循环统计量方法在滚动轴承故障诊断中的应用[J].振动、测试与诊断,2003,23:116-119.LI Li,QU Liang-sheng.Application of cyclic statistics to fault diagnosis of rolling bearings[J].Journal of Vibration,Measurement&Diagnosis,2003,23:116-119.
[8]姜鸣.循环统计量理论及其在滚动轴承故障诊断中的应用研究[D].上海:上海交通大学,2002.
[9]周福昌.基于循环平稳信号处理的滚动轴承故障诊断方法研究[D].上海:上海交通大学,2006.
[10]明阳.基于循环平稳和盲源分离的滚动轴承故障特征提取方法研究[D].上海:上海交通大学,2013.
[11]Han Y S,Lee C W.Directional Wigner distribution for order analysis in rotating/reciprocating machines[J].Mechanical Systems and Signal Processing,1999,13(5):723-737.
[12]毕果.基于循环平稳的滚动轴承及齿轮微弱故障特征提取应用研究[D].上海:上海交通大学,2007.
[13]沈庆,郑水英.设备故障诊断[M].北京:化学工业出版社,2006.
[14]屈梁生.机械故障的全息诊断原理[M].北京:科学出版社,2007.
[15]Gardner W A.Stationarizable random processes[J].IEEE Transactions on Information Theory,1978,24:8-22.
[2]彭畅,柏林,谢小亮.基于EEMD,度量因子和快速峭度图的滚动轴承故障诊断方法[J].振动与冲击,2012,31(20):143-146.PENG Chang,BO Lin,XIE Xiao-liang.Fault diagnois method ofrolling element bearing based on EEMD,measurefactor and fast kurtogram[J].Journal of Vibration and Shock,2012,31(20):143-146.
[3]毕果.基于循环平稳的滚动轴承及齿轮微弱故障特征提取应用研究[D].上海:上海交通大学,2007.
[4]Capdessus C,Sidahmed M,Lacoume J L.Cyclostationary processes:application in gear faults early diagnosis[J].Mechanical Systems and Signal Processing,2000,14:371-385.
[5]Mccormick A C,Nandi A K.Cyclostationarity in rotating machine vibrations[J].Mechanical System and Signal Processing,1998,12(2):225-242.
[6]Randall R B,Antoni J,Chobsaard S.The relationship between spectral correlation and envelope analysis in the diagnostics of bearing faults and other cyclostationary machine signals[J].Mechanical Systems and Signal Processing,2001,15:945-962.
[7]李力,屈梁生.循环统计量方法在滚动轴承故障诊断中的应用[J].振动、测试与诊断,2003,23:116-119.LI Li,QU Liang-sheng.Application of cyclic statistics to fault diagnosis of rolling bearings[J].Journal of Vibration,Measurement&Diagnosis,2003,23:116-119.
[8]姜鸣.循环统计量理论及其在滚动轴承故障诊断中的应用研究[D].上海:上海交通大学,2002.
[9]周福昌.基于循环平稳信号处理的滚动轴承故障诊断方法研究[D].上海:上海交通大学,2006.
[10]明阳.基于循环平稳和盲源分离的滚动轴承故障特征提取方法研究[D].上海:上海交通大学,2013.
[11]Han Y S,Lee C W.Directional Wigner distribution for order analysis in rotating/reciprocating machines[J].Mechanical Systems and Signal Processing,1999,13(5):723-737.
[12]毕果.基于循环平稳的滚动轴承及齿轮微弱故障特征提取应用研究[D].上海:上海交通大学,2007.
[13]沈庆,郑水英.设备故障诊断[M].北京:化学工业出版社,2006.
[14]屈梁生.机械故障的全息诊断原理[M].北京:科学出版社,2007.
[15]Gardner W A.Stationarizable random processes[J].IEEE Transactions on Information Theory,1978,24:8-22.