Analysis of the Condition Based Monitoring System for Heavy Industrial Machineries

被引:0
作者
Agrawal, Krishna Kant [1 ]
Pandey, G. N. [1 ,2 ]
Chandrasekaran, Kannan [3 ]
机构
[1] Indian Inst Informat Technol, Allahabad, Uttar Pradesh, India
[2] Arunachal Univ Studies, Mile, Arunachal Prade, India
[3] Indian Oil Corp Ltd, CRM Appl Met & Pipeline Res, Ctr Res & Dev, Faridabad, India
来源
2013 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND COMPUTING RESEARCH (ICCIC) | 2013年
关键词
CBM; Vibration analysis; Predictive maintenance;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Condition monitoring of Industrial machines typically relies on being able to detect the disparity between a healthy machine and a faulty one. An accurate interpretation of a machine's condition requires knowledge of the effects of different operating conditions. Phrase Condition monitoring is sometimes used in combination with predictive maintenance which is maintenance of machines based on a signature that a problem is about to occur. In current scenario many industries is replacing predictive maintenance with run-to-breakdown maintenance and in some cases with preventive maintenance, where mechanical parts are replaced periodically regardless of the machinery mechanical condition. There are a lot of practices available and discussed in this paper for condition monitoring but measuring vibration is one of the most essential in detecting and diagnoses any deviation from usual machine conditions. Vibration monitoring of Machinery is the most effectual technique, used to track operating conditions of machines which will further reduce maintenance costs and subsequent downtime caused by catastrophic failure of machineries of the Industry simultaneously. This Research ponders upon different condition based monitoring techniques available and state of the art development for identifying the most effective technique in diverse scenarios.
引用
收藏
页码:602 / 605
页数:4
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