Basic research on machinery fault diagnostics: Past, present, and future trends

被引:107
作者
Chen, Xuefeng [1 ,2 ]
Wang, Shibin [1 ,2 ]
Qiao, Baijie [1 ,2 ]
Chen, Qiang [1 ,2 ]
机构
[1] Xi An Jiao Tong Univ, State Key Lab Mfg Syst Engn, Xian 710049, Shaanxi, Peoples R China
[2] Xi An Jiao Tong Univ, Sch Mech Engn, Xian 710049, Shaanxi, Peoples R China
基金
中国国家自然科学基金;
关键词
fault diagnosis; fault mechanism; feature extraction; signal processing; intelligent diagnostics; ROLLING-ELEMENT BEARINGS; EMPIRICAL MODE DECOMPOSITION; WAVELET FINITE-ELEMENT; CYLINDRICAL ROLLER BEARING; LOCAL MEAN DECOMPOSITION; HILBERT-HUANG TRANSFORM; TIME-FREQUENCY ANALYSIS; MATCHING DEMODULATION TRANSFORM; OPTIMIZED SPECTRAL KURTOSIS; TURBINE PLANETARY GEARBOX;
D O I
10.1007/s11465-018-0472-3
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Machinery fault diagnosis has progressed over the past decades with the evolution of machineries in terms of complexity and scale. High-value machineries require condition monitoring and fault diagnosis to guarantee their designed functions and performance throughout their lifetime. Research on machinery Fault diagnostics has grown rapidly in recent years. This paper attempts to summarize and review the recent R&D trends in the basic research field of machinery fault diagnosis in terms of four main aspects: Fault mechanism, sensor technique and signal acquisition, signal processing, and intelligent diagnostics. The review discusses the special contributions of Chinese scholars to machinery fault diagnostics. On the basis of the review of basic theory of machinery fault diagnosis and its practical applications in engineering, the paper concludes with a brief discussion on the future trends and challenges in machinery fault diagnosis.
引用
收藏
页码:264 / 291
页数:28
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