NDLI: Application of reliability-centered stochastic approach and FMECA to conditional maintenance of electric power plants in China

Content Provider	IEEE Xplore Digital Library
Author	Cheng Yun Chung, T.S. Yu, C.W. Chung, C.Y. Zeng Ming Sun Xin
Copyright Year	2004
Description	Author affiliation: Dept. of Electr. Eng., Hong Kong Polytech. Univ., Kowloon, China (Cheng Yun; Chung, T.S.; Yu, C.W.; Chung, C.Y.)
Abstract	In a competitive supply-side power market, conditional maintenance can help the generation utilities to reduce cost and gain more profit. In this paper, reliability-centered maintenance (RCM) analytical method is adopted. The reliability-based mathematical model for predicting the failures of the subsystems and components in the power plant is established, and the failure mechanism is studied. Software is developed to simulate the failures evolution and forecast their tendency. Based on the above and further ranking the weightiness of equipment whose status to be observed by FMECA (failure mode effects & criticality analysis), the power plant manager may choose appropriate condition monitoring and failure diagnosis apparatus for carrying out conditional maintenance. At the end of this paper, some suggestions on the reformation of equipment maintenance plan and pattern in China are proposed. In this paper, practical research on four 200 MW generation units of Junliangcheng power plant in China is implemented. The results show that it can efficiently help decreasing the cost on maintenance and hence improve the total benefit.
Starting Page	463
Ending Page	467
File Size	372526
Page Count	5
File Format	PDF
ISBN	0780382374
DOI	10.1109/DRPT.2004.1338018
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-04-05
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Stochastic processes Maintenance Power generation Costs Failure analysis Power supplies Power markets Mathematical model Predictive models Energy management
Content Type	Text
Resource Type	Article

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