Abstract:Aiming at that diesel engine crankshaft bearing wear fault signals’ characteristics are very weak, they are easy to be buried by noise and signals of different fault levels are hard to be distinguished, a new information entropy enhancement method based on the synchro-squeezed wavelet transform and locally preserving projection was proposed. Firstly, a signal was reconstructed in multi-scale mode with the synchro-squeezed wavelet transform. Then the dimensions of the multi-scale signal were reduced with the locally preserving projection to eliminate its redundant information and enhance its impact characteristic. Finally, three information entropies in time domain, frequency domain and time-frequency domain were used to characterize the signal features. Simulated and actual signals showed that the proposed method can enhance the fault signals’ features obviously, and realize classification recognition of crankshaft wear states according to information entropy values.
吴春志1,贾继德1,贾翔宇1,张帅1. 基于多尺度降维的柴油机信号信息熵增强方法[J]. 振动与冲击, 2018, 37(3): 180-185.
WU chunzhi1, JIA Jide1, JIA Xiangyu1, ZHANG Shuai 1. A method to enhance information entropy of diesel engine signals based on multi-scale dimension reduction. JOURNAL OF VIBRATION AND SHOCK, 2018, 37(3): 180-185.
[1] 夏天,王新晴,赵慧敏等.基于高阶累积量的柴油发动机曲轴轴承故障特征提取[J].振动与冲击,2011,30(1):77-81
XIA T, WANG XQ, ZHAO HM et al. Extracting fault features of a Diesel engine's crankshaft bearing based on high-order cumulation[J]. JOURNAL OF VIBRATION AND SHOCK, 2011,30(1):77-81.
[2] 沈虹,赵红东,张玲玲等.基于EMD和Gabor变换的发动机曲轴轴承故障特征提取[J].汽车工程, 2014,(12):1546-1550.
SHEN H, ZHAO HD, ZHANG LL, et al. Fault Feature Extraction of Engine Crankshaft Bearing Based on EMD and Gabor Transform[J]. Automotive Engineering, 2014,(12):1546-1550.
[3] 贾继德,张玲玲,梅检民等.非平稳循环特征极坐标增强及其在发动机故障诊断中的应用[J].振动工程学,2013,26(6):960-964.
JIA JD, ZHANG LL, MEI JM, et al. Polar coordinate enhancement of non-stationary circling characteristic for engine fault diagnosis[J]. Journal of Vibration Engineering, 2013,26(6):960-964.
[4] YAN YJ, Yu JC, GUO PF, et cl. Utility analysis and evaluation method study of side channel information [J].Journal of Electronics (China), 2013, 30(5):500-508.
[5] ZHANG P, TANG HW, YAO WY, et cl. Experimental investigation of morphological characteristics of rill evolution on loess slope[J]. Catena, 2016,137: 536-544.
[6] 龙英,何怡刚,张镇等.基于信息熵和Haar小波变换的开关电流电路故障诊断新方法[J].仪器仪表学报,2015,36(3):701-711.
LONG Y, HE YG, ZHANG Z, et al. Switched-current circuit fault diagnosis based on entropy and Haar wavelet transform[J]. Chinese Journal of Scientific Instrument, 2015,36(3):701-711.
[7] 黎敏,阳建宏,王晓景等.基于信息熵的循环谱分析方法及其在滚动轴承故障诊断中的应用[J].振动工程学报,2015,28(1):164-174.
LI M, YANG JH, WANG XJ et al. The cyclic spectrum density method based on entropy and its application to the fault diagnosis of rolling bearings[J]. Journal of Vibration Engineering, 2015,28(1):164-174.
[8] Daubechies I, Lu J, Wu H T, Synchrosqueezed wavelet transforms: An empirical mode decompose- tion-like tool: Applied and Computational Harmonic Analysis[J], 2011, 30:243-261.
[9] Yu JB. Bearing performance degradation assessment using locality preserving projections and Gaussian mixture models[J]. Mechanical Systems and Signal Processing,2011,25(7):2573-2588.
[10] 丁晓喜,何清波. 基于WPD和LPP的设备故障诊断方法研究[J].振动与冲击,2014,03:89-93.
DING XX, HE QB. Machine fault diagnosis based on WPD and LPP[J]. Journal of Vibration and Shock, 2014,03:89-93.
[11] Daubechies I, Maes S. A nonlinear squeezing of the continuous wavelet transform based onauditory nerve
models[J]. in Wavelets in Medicine and Biology, 1996: 527-546.
[12] Sheen YT.A complex filter for vibration signal demodulation in bearing defect diagnosis[J].Journal of Sound and Vibration,2004,276(1):105-119.
[13] 张晓涛,唐力伟,王平等.基于多尺度局部保持投影的轴承故障特征增强方法[J].噪声与振动控制,2014,(6):166-168,173.
ZHANG XT, TANG LW, WANG P, et al. Bearing Fault Feature Enhancement Method Based on Multi-scale Locality Preserving Projection[J]. Noise and Vibration Control, 2014,(6):166-168,173.
[14] CAI D, HE X, HAN J. Document clustering using locality preserving indexing[J]. IEEE Transactions on Knowledge and Data Engineering, 2005, 17(12).
[15] Shannon C E. A mathematical theory of communica-tion[J].AcM SIGMOBILE Mobile computing and Communications Review,1948,5(1):3-55.
[16] Shen Tao,黄树红,韩守木等.旋转机械振动信号的信息熵特征[J].机械工程学报,2001, 37(6): 94-98.
SHEN T, HUANG SH, HAN SM, et al. Extracting information entropy features for rotating machinery vibration signals[J]. CHINESE JOURNAL OF MECHANICAL ENGINEERING.2001, 37(6): 94-98.