Spectral kurtosis for fault detection, diagnosis and prognostics of rotating machines: A review with applications

被引:404
作者
Wang, Yanxue [1 ,2 ]
Xiang, Jiawei [3 ]
Markert, Richard [2 ]
Liang, Ming [4 ]
机构
[1] Guilin Univ Elect Technol, Sch Mech Engn, Guilin 541004, Peoples R China
[2] Tech Univ Darmstadt, Strukturdynam, D-64287 Darmstadt, Germany
[3] Wenzhou Univ, Coll Mech & Elect Engn, Wenzhou 325035, Peoples R China
[4] Univ Ottawa, Dept Mech Engn, Ottawa, ON K1N 6N5, Canada
基金
中国国家自然科学基金;
关键词
Spectral kurtosis; Rotating machines; Fault diagnosis; Prognostics; ROLLING ELEMENT BEARINGS; TIME-FREQUENCY ANALYSIS; ACOUSTIC-EMISSION; DAMAGE DETECTION; SIGNAL; GEAR; PERFORMANCE; KURTOGRAM; SELECTION; MODEL;
D O I
10.1016/j.ymssp.2015.04.039
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Condition-based maintenance via vibration signal processing plays an important role to reduce unscheduled machine downtime and avoid catastrophic accidents in industrial enterprises. Many machine faults, such as local defects in rotating machines, manifest themselves in the acquired vibration signals as a series of impulsive events. The spectral kurtosis (SK) technique extends the concept of kurtosis to that of a function of frequency that indicates how the impulsiveness of a signal. This work intends to review and summarize the recent research developments on the SK theories, for instance, short-time Fourier transform-based SK, kurtogram, adaptive SK and protrugram, as well as the corresponding applications in fault detection and diagnosis of the rotating machines. The potential prospects of prognostics using SK technique are also designated. Some examples have been presented to illustrate their performances. The expectation is that further research and applications of the SK technique will flourish in the future, especially in the fields of the prognostics. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:679 / 698
页数:20
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