Early Performance Degradation Assessment of Rolling Bearings Based on Comprehensive Evaluation Function Constructing by Wavelet Packet Energy Spectrum

Abstract

Abstract:

The traditional time-frequency characteristics was not obvious in the early degradation extraction of the rolling bearings so this paper put forward a method based on wavelet packet energy spectrum in combination with principal component analysis for the early degradation extraction.First using normal signal data the wavelet packet energy spectrum was acquireal, then the principal component analysis was used to achieve dimension reduction for the high dimensional feature vector. Finally through the principal component analysis the comprehensive evaluation function was constructed,which was used to achieve the early degradation extraction of the rolling bearings.

Key words: wavelet packet energy spectrum;principal component analysis;early degradation assessment, comprehensive evaluation function

摘要：

针对传统的时域、频域特征不能明显地表征滚动轴承的早期退化特征的问题，提出了一种小波包能量谱结合主成分分析构建综合评估函数的滚动轴承早期性能退化评估方法。该方法以采集到的轴承正常工作时的振动信号作为训练样本，对样本进行小波包能量谱计算，得到高维特征向量;再利用主成分分析方法降维并建立综合评估函数对早期性能退化区的数据进行判断。运用实测的滚动轴承全寿命实验数据进行检验，结果表明该方法能实现对滚动轴承早期性能退化的评估。

关键词: 小波包能量谱, 主成分分析, 早期退化评估, 综合评估函数

CLC Number:

TP391
TH132

Yang Fan, Tang Baoping, Yin Aijun. Early Performance Degradation Assessment of Rolling Bearings Based on Comprehensive Evaluation Function Constructing by Wavelet Packet Energy Spectrum[J]. China Mechanical Engineering, 2015, 26(17): 2355-2368.

杨帆, 汤宝平, 尹爱军. 小波包能谱构建综合评估函数的轴承退化评估[J]. 中国机械工程, 2015, 26(17): 2355-2368.

References

[1]肖文斌, 陈进, 周宇, 等. 小波包变换和隐马尔可夫模型在轴承性能退化评估中的应用[J]. 振动与冲击, 2011, 30(8): 32-35.
Xiao Wenbing, Chen Jin, Zhou Yu,et al.Wavelet Packet Transform and Hidden Markov Model Based Bearing Performance Degradation Assessment[J]. Journal of Vibration and Shock, 2011, 30(8):32-35.
[2]Pan Y, Chen J, Li X. Bearing Performance Degradation Assessment Based on Lifting Wavelet Packet Decomposition and Fuzzy c-means[J]. Mechanical Systems and Signal Processing, 2010, 24(2): 559-566.
[3]Pan Y, Chen J, Guo L. Robust Bearing Performance Degradation Assessment Method Based on Improved Wavelet Packet-support Vector Data Description[J]. Mechanical Systems and Signal Processing, 2009, 23(3): 669-681.
[4]Tang B, Liu W, Song T. Wind Turbine Fault Diagnosis Based on Morlet Wavelet Transformation and Wigner-ville Distribution[J]. Renewable Energy, 2010, 35(12): 2862-2866.
[5]龙凯, 李刚成.基于Hilbert变换与威布尔分布的轴承早期故障诊断[J]. 科学技术与工程, 2010 (17): 4163-4167.
Long Kai, Li Gangcheng. A Method of Incipient Fault Diagnosis for Rolling Bearing Based on Hilbert Transform and Weibull Distribution[J]. Science technology and Engineering, 2010(17):4163-4167.
[6]郭磊, 陈进. 小波包熵在设备性能退化评估中的应用[J]. 机械科学与技术, 2008, 27(9): 1203-1206.
Guo lei, Chen Jin. Application of Wavelet Packet Entropy to Equipment Performance Degradation Assessment[J]. Mechanical Science and Technology for Aerospace Engineering, 2008,27(9):1023-1026.
[7]陈军堂, 廖世勇, 甘剑锋, 等. 小波包能量谱在内燃机噪声信号故障诊断中的应用[J]. 内燃机, 2010(5): 46-48.
Chen Juntang, Liao Shiyong, Gan Jianfeng, et al. The Application of the Wavelet Packet Energy Spectrum in Fault Diagnosis of I.C.E. Noise Signal[J]. Internal Combustion Engine,2010（5）:46-49.
[8]贺银芝, 应怀樵. 小波包分解及其能量谱在发动机连杆轴承故障诊断中的应用[J]. 振动工程学报, 2001, 14(1): 72-75.
He Yinzhi, Ying Huaijiao. Application of Wavelet Packet Decomposition and Its Energy Spectrum on the Fault Diagnosis of Reciprocation Machinery[J]. Journal of Vibration Engineering, 2001,14(1):72-75.
[9]肖健华, 吴今培, 樊可清, 等. 粗糙主成分分析在齿轮故障特征提取中的应用[J]. 振动工程学报, 2003, 16(2): 166-170.
Xiao Jianhua, Wu Jinpei, Fan Keqing, et al. Rough Principal Component Analysis and Its Application on Feature Extraction for Gears[J]. Journal of Vibration Engineering, 2003,16(2):166-170.
[10]Dong S, Luo T. Bearing Degradation Process Prediction Based on the PCA and Optimized LS-SVM Model[J]. Measurement, 2013, 46(9): 3143-3152.
[11]王楠, 律方成. 基于小波变换的介损在线监测数据趋势提取[J]. 高电压技术, 2003, 29(3): 31-33.
Wang Nan, Lü Fangcheng. Application of Wavelet Transform to Extract the Trend of On-line Monitoring[J]. High Voltage Engineering, 2003, 29(3):31-33.
[12]Lee J, Qiu H, Yu G, et al. Rexnord Technical Services, “Bearing Data Set”,IMS, University of Cincinnati, NASA Ames Prognostics Data Repository, <http://ti.arc.nasa.gov/project/prognostics-data-repository>, NASA Ames, Moffett Field, CA, 2007.

[1]	LI Rongqi, YAN Tao, HE Zhicheng, MI Dong, JIANG Chao, ZHENG Jing. A Topology Optimized Design Method for High-performance Structures with Fluid-thermal-mechanics Coupling [J]. China Mechanical Engineering, 2024, 35(03): 487-497.
[2]	MEI Jie, QIN Jiarui, CHEN Dingfang, CHEN Kun, . SLAM-based Underwater Image Enhanced Visual 3D Reconstruction Method [J]. China Mechanical Engineering, 2024, 35(02): 268-279.
[3]	XIAO Gang, GU Hairui, DONG Jinjin, WANG Qibing, LU Jiawei. Simulation Data-driven Migration Diagnosis Method for Guide Rail Faults in Long-term Service Elevators [J]. China Mechanical Engineering, 2024, 35(01): 125-135.
[4]	LIU Xiaobao, YAN Qingxiu, YI Bin, YAO Tingqiang, GU Wenjuan. Optimization of Process Parameters in Process Manufacturing Based on Ensemble Learning and Improved Particle Swarm Optimization Algorithm [J]. China Mechanical Engineering, 2023, 34(23): 2842-2853.
[5]	GUO Jutao, LYU Youlong, DAI Zheng, ZHANG Jie, GUO Yu. Compound Rules and Reinforcement Learning Based Scheduling Method for Mixed Model Assembly Lines [J]. China Mechanical Engineering, 2023, 34(21): 2600-2606,2614.
[6]	WU Dianjian, ZHANG Sanqiang, YANG Guangyou, . Optimal Layout Method of 2D Irregular Parts under Complex Cutting Process Constraints [J]. China Mechanical Engineering, 2023, 34(21): 2615-2621.
[7]	JIANG Shikuo, WANG Xiaoping, WANG Kai, JIN Jiang. Fixed-angle Method for Examines Automatic Fiber Placement Based on Point Cloud Surfaces [J]. China Mechanical Engineering, 2023, 34(21): 2629-2636,2645.
[8]	WANG Wei, JI Xiaogang, FANG Chuang, NIU Guofa. Fatigue Life Prediction of Flexible Lattice Structures Prepared by Digital Light Process [J]. China Mechanical Engineering, 2023, 34(21): 2637-2645.
[9]	ZHANG Yuhang, SUN Yuwen, XU Jinting. Hybrid Algorithm of Machining Feature Segmentation and Recognition for Aero-engine Casings [J]. China Mechanical Engineering, 2023, 34(20): 2475-2481.
[10]	XUE Kai, GUO Runlan, HUANG Huiyang, HUANG Hua. Structural Optimization Method of Additive Manufacturing Model Based on Point Cloud Data [J]. China Mechanical Engineering, 2023, 34(20): 2482-2488.
[11]	XU Meijiao, XUE Shanliang, ZHANG Hui, ZHOU Guoqing, LU Honggen. Manufacturing Readiness Level Assessment Method of Complex Product Assembly Based on BP-AdaBoost Algorithm [J]. China Mechanical Engineering, 2023, 34(20): 2513-2519.
[12]	TWANG Wei, MA Qianlun, BAI Zhenhua, WANG Ziang. Mechanics Property Prediction of Cold Rolled High Strength Steel Coils Based on GBD#br# [J]. China Mechanical Engineering, 2023, 34(18): 2222-2229.
[13]	WANG Liting, TANG Zhao, LI Rong, GU Zheng, HU Yuwei, LI Yuehong, ZHANG Jiye. Collaborative Visualization Analysis of Train Dynamics by Cloud Simulation-driven [J]. China Mechanical Engineering, 2023, 34(18): 2248-2256.
[14]	ZHU Sipei, FU Guoqiang, ZHENG Yue, LI Zhengtang, YANG Jixiang. Universal Surface Texture Modeling Method for Five-axis Surface Milling [J]. China Mechanical Engineering, 2023, 34(16): 1946-1957.
[15]	SUN Hao, YUAN Ye, ZHANG Qi, ZHANG Xiaobei. Path Planning Method of Aviation Cables Based on Improved A* Algorithm [J]. China Mechanical Engineering, 2023, 34(16): 1958-1964,1974.