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

作     者：Wan Zhang Min-Ping Jia Lin Zhu Xiao-An Yan 

作者机构：School of Mechanical Engineering Southeast UniversityNanjing 211189 China 

出 版 物：《Chinese Journal of Mechanical Engineering》 (中国机械工程学报（英文版）)

年 卷 期：2017年第30卷第4期

页      面：782-795页

核心收录：

学科分类：0817[工学-化学工程与技术] 08[工学] 0807[工学-动力工程及工程热物理] 0802[工学-机械工程] 0811[工学-控制科学与工程] 0801[工学-力学（可授工学、理学学位）] 080201[工学-机械制造及其自动化] 

基　　金：Supported by National Natural Science Foundation of China(Grant No.51675098) 

主　　题：Computational intelligence Machinerycondition monitoring Fault diagnosis Neural networkFuzzy logic Support vector machine - Evolutionaryalgorithms 

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 com- prehensive reviews have summarized the ongoing efforts of computational intelligence in machinery condition moni- toring and fault diagnosis. The recent research and devel- opment 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 dis- cussed. 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 mech- anism, improving algorithm efficiency and enhancing engineering application. This review may be considered as a useful guidance for researchers in selecting a suit- able method for a specific situation and pointing out potential research directions.