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Neural Network Based Hydraulic Engineering Machinery Fault Diagnosis Expert System Research and Implementation

Author: HanBin
Tutor: ChenXinXuan
School: Chang'an University
Course: Mechanical Design and Theory
Keywords: Hydraulic system Intelligent Diagnosis Neural Network Expert System ANNES
CLC: TH137
Type: Master's thesis
Year: 2005
Downloads: 616
Quote: 7
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Abstract


Hydraulic system with its small size , light weight , high power , smooth and can achieve a large range of variable speed , etc., are widely used in engineering machinery, power, control and execution systems . However, the hydraulic system , poor working conditions and intuitive , easy access to parameters , fault has multiple , uncertainty and invisibility ; hydraulic system fault symptoms and cause of the fault exists between the complex nonlinear relationship , which can not be described simply as a function of to classical fault diagnosis technology makes it difficult , but based on neural networks and intelligent diagnostic expert system technology a good solution to the problem, making the diagnosis more accurate and reliable results . This comprehensive analysis of the current variety of hydraulic system fault diagnosis techniques and methods for the characteristics of the hydraulic system failure is established based on neural network fault diagnosis expert system hydraulic pressure (ANNES) models and components of the system ( knowledge storage systems , learning systems , inference engine , interpreter and interactive interface ) the detailed structure and design methods . Finally excavator hydraulic system based on the realization ANNES fault diagnosis , fault diagnosis proved the feasibility of the method . ANNES combines adaptive learning ability of neural networks and expert systems knowledge representation definite advantages to simplify data acquisition and learning neural network expert system inference rule creation process. ANNES working process are: ① first establish a knowledge base ; ② learning system to acquire knowledge , it only requires experts to provide an example ( or examples ) and the corresponding solutions, through neural network learning algorithm to learn the sample through adaptive algorithm within the network constantly revised weight distribution in order to meet the requirement, the expert heuristic for solving practical problems of knowledge and experience to the network interconnection and distribution of weight distribution ; ③ inference machine based on the knowledge in knowledge and the fact that users of reasoning ; ④ forward through the neural network calculation , to obtain an output vector at the output terminal : ⑤ the expert system

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CLC: > Industrial Technology > Machinery and Instrument Industry > Mechanical parts and gear > Hydraulic transmission
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