NDLI: Research and development of equipment failure prognostic system based on similarity modeling

Content Provider	IEEE Xplore Digital Library
Author	Lv Yukun Zhu Wen Chang Shuping Guo Jianglong
Copyright Year	2012
Description	Author affiliation: Department of Power Engineering, North China Electric Power University, NCEPU, Baoding, China (Lv Yukun) \|\| Department of Automation, North China Electric Power University, NCEPU, Baoding, China (Zhu Wen) \|\| Thermal dynamic technology institute, Hebei Electric Power Research Institute, Shijiazhuang, China (Chang Shuping; Guo Jianglong)
Abstract	The cost of equipment maintains accounts for a great proportion in the operation cost per year in the power plant. The equipment failure will cause enormous loss. If we could find out the signs of faults as early as possible, we can take effective measures to avoid the negative consequences. Alter the forced maintains into active ones, changing non-plan halt to planned halt. By this means, we can reduce the times of equipment failure to the least, prolong maintains intervals, decrease the time for maintains. So that the expanse of maintains can be reduced, the property of equipment can be improved, and the cost of fuels also can be saved. Meanwhile, the accountability and availability of the generators and the income of electricity sales can be raised up, which contributes to the less fines.
Starting Page	1
Ending Page	4
File Size	459118
Page Count	4
File Format	PDF
ISBN	9781467344975
ISSN	21544824
e-ISBN	9781889334479
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-24
Publisher Place	Mexico
Access Restriction	Subscribed
Rights Holder	TSI Press
Subject Keyword	Data models Monitoring Production facilities Real-time systems Predictive models Power generation Information systems Failure diagnosis Similarity Modeling Failure Prognostic
Content Type	Text
Resource Type	Article

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