文献详情
Detrended Fluctuation Analysis and Hough Transform Based Self-Adaptation Double-Scale Feature Extraction of Gear Vibration Signals
作者Wang, JiaQing[1];Xiao, Han[2];Lv, Yong[3];Wang, Tao[4];Xu, Zengbing[5]
文献类型期刊
机构
通讯作者Xiao, H (reprint author), Wuhan Univ Sci & Technol, Hubei Prov Key Lab Machine Transmiss & Mfg Engn, POB 222, Wuhan 430081, Hubei, Peoples R China.
期刊名称SHOCK AND VIBRATION影响因子和分区
2016
2016
增刊正刊
收录情况SCI(E)(WOS:000370400200001)  EI(20160501869458)  
期刊等级B
所属部门机械自动化学院;研究生院
百度学术Detrended Fluctuation Analysis and Hough Transform Based Self-Adaptation Double-Scale Feature Extraction of Gear Vibration Signals
语言外文
ISSN1070-9622
DOI10.1155/2016/3409897
被引频次1
人气指数47
浏览次数34
基金National Natural Science Foundation of China (NSFC) [51105284, 51475339, 51375154, 51405353]
摘要This paper presents the analysis of the vibration time series of a gear system acquired by piezoelectric acceleration transducer using the detrended fluctuation analysis (DFA). The experimental results show that gear vibration signals behave as double-scale characteristics, which means that the signals exhibit the self-similarity characteristics in two different time scales. For further understanding, the simulation analysis is performed to investigate the reasons for double-scale of gear's fault vibration signal. According to the analysis results, a DFA double logarithmic plot based feature vector combined with scale exponent and intercept of the small time scale is utilized to achieve a better performance of fault identification. Furthermore, to detect the crossover point of two time scales automatically, a new approach based on the Hough transform is proposed and validated by a group of experimental tests. The results indicate that, comparing with the traditional DFA, the faulty gear conditions can be identified better by analyzing the double-scale characteristics of DFA. In addition, the influence of trend order of DFA on recognition rate of fault gears is discussed.
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