NDLI: Fault diagnosis of oil pump based on high speed and precise genetic algorithm neural network

Content Provider	IEEE Xplore Digital Library
Author	Meijuan Gao Jingwen Tian Liting Cao Jin Xu
Copyright Year	2008
Description	Author affiliation: Dept. of Autom. Control, Beijing Union Univ., Beijing (Meijuan Gao; Jingwen Tian; Liting Cao) \|\| Sch. of Inf. Sci., Beijing Univ. of Chem. Technol., Beijing (Jin Xu)
Abstract	Considering the issues that the relationship between the fault of oil pump existent and fault information is a complicated and nonlinear system, and it is very difficult to found the process model to describe it. According to the physical circumstances of oil pump, a fault diagnosis method of oil pump based on high speed and precise genetic algorithm neural network is presented in this paper. The high speed and precise genetic algorithm neural network is combined the adaptive and floating-point code genetic algorithm with BP which has higher accuracy and faster convergence speed. With the ability of strong self-learning and function approach and fast convergence rate of high speed and precise genetic algorithm neural network, the diagnosis method can truly diagnose the fault of oil pump by learning the fault information of oil pump. The real diagnosis results show that this method is feasible and effective.
Starting Page	965
Ending Page	970
File Size	388468
Page Count	6
File Format	PDF
ISBN	9781424416738
DOI	10.1109/ICCIS.2008.4670935
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-09-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fault diagnosis Petroleum Genetic algorithms Neural networks Costs Convergence Production Pumps Information science Chemical technology fault diagnosis genetic algorithms neural network oil pump
Content Type	Text
Resource Type	Article

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