摘要
Condition monitoring is increasingly used to anticipate and detect failures of industrial machines.Failures of machines can cause high maintenance or replacement costs.If neglected,it may result in catastrophic accidents leading to production shrinkage.The potential failure would negatively affect the profitability of the company,including production shut down,cost of spare parts,cost of labor,damage of reputation,risk of injury to people and the environment.In recent years,condition-based maintenance( CBM) and prognostic and health management( PHM) are developed and formed a strong connection among science,engineering,computer,reliability,communication,management,etc.Computerized maintenance management systems( CMMS) store a lot of data regarding the fault diagnosis and life prediction of the machinery equipment.It's too necessary to uncover useful knowledge from the huge amount of data.It's vital to find the ways to obtain useful and concise information from these data.This information can be of great influence in the decision making of managers.This article is a review of intelligent approaches in machinery faults diagnosis and prediction based on PHM and CBM.
Condition monitoring is increasingly used to anticipate and detect failures of industrial machines.Failures of machines can cause high maintenance or replacement costs.If neglected,it may result in catastrophic accidents leading to production shrinkage.The potential failure would negatively affect the profitability of the company,including production shut down,cost of spare parts,cost of labor,damage of reputation,risk of injury to people and the environment.In recent years,condition-based maintenance（ CBM） and prognostic and health management（ PHM） are developed and formed a strong connection among science,engineering,computer,reliability,communication,management,etc.Computerized maintenance management systems（ CMMS） store a lot of data regarding the fault diagnosis and life prediction of the machinery equipment.It＇s too necessary to uncover useful knowledge from the huge amount of data.It＇s vital to find the ways to obtain useful and concise information from these data.This information can be of great influence in the decision making of managers.This article is a review of intelligent approaches in machinery faults diagnosis and prediction based on PHM and CBM.
作者
奥米迪.欧利
刘淑杰
OMIDI Ali;LIU Shujie(School of Mechanical Engineering,Dalian University of Technology,Dalian 116024,China)
基金
Fundamental Research Funds for the Central Universities,China(No.DUT17GF214)
关键词
工业机器
设备故障
预防措施
管理模式
condition-based maintenance（CBM） prognostic and health management（PHM） machinery fault diagnosis data mining data processing
