Comprehensive Overview on Computational Intelligence Techniques for Machinery Condition Monitoring and Fault Diagnosis

Chinese Journal of Mechanical Engineering

Xiao-An Yan¹  Min-Ping Jia¹  Lin Zhu¹  Wan Zhang¹ 

[1] School of Mechanical Engineering, Southeast University, 211189, Nanjing, China;

关键词: Computational intelligence;    Machinery condition monitoring;    Fault diagnosis;    Neural network;    Fuzzy logic;    Support vector machine;    Evolutionary algorithms;   

DOI  :  10.1007/s10033-017-0150-0

来源: Springer

【 摘 要 】

Computational intelligence is one of the most powerful data processing tools to solve complex nonlinear problems, and thus plays a significant role in intelligent fault diagnosis and prediction. However, only few comprehensive reviews have summarized the ongoing efforts of computational intelligence in machinery condition monitoring and fault diagnosis. The recent research and development of computational intelligence techniques in fault diagnosis, prediction and optimal sensor placement are reviewed. The advantages and limitations of computational intelligence techniques in practical applications are discussed. The characteristics of different algorithms are compared, and application situations of these methods are summarized. Computational intelligence methods need to be further studied in deep understanding algorithm mechanism, improving algorithm efficiency and enhancing engineering application. This review may be considered as a useful guidance for researchers in selecting a suitable method for a specific situation and pointing out potential research directions.

【 授权许可】

CC BY