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A Study on Fault Diagnosis Based on Fault-tolerant Neural Network

Author: XuBaiLing
Tutor: LiuQun
School: Harbin Engineering University
Course: Applied Computer Technology
Keywords: Fault Diagnosis Information Fusion Neural Networks Fault-tolerant
CLC: TP183
Type: Master's thesis
Year: 2005
Downloads: 411
Quote: 3
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Abstract


Equipment fault diagnosis technology developed in nearly 40 years to adapt to the engineering needs a multidisciplinary , interdisciplinary inevitable development , and thereby acquire very significant economic benefits . Data fusion as many traditional disciplines and emerging engineering fields combined produce a new frontier disciplines and beyond in the military field , has been widely applied in many fields . A lot of information available equipment fault diagnosis , and only take full advantage of the useful information to diagnose equipment failures in order to improve the accuracy and reliability of the fault diagnosis , fault diagnosis is essentially a multi- information fusion process . In this paper, based on artificial neural network information fusion fault diagnosis , analysis of the list of the neural network fault Jane off characteristics , integrated neural network fault diagnosis model , integrated neural network modeling method established principle and implementation strategy combined diagnosis instance simulation analysis , results show that the integrated neural network information fusion fault diagnosis is an effective method . Equipment fault diagnosis , and how to reduce the rate of misdiagnosis of great significance to improve the reliability of the study . Traditional diagnostic system does not consider the error of the output of the network in the case of the role of various disturbances or failure , the fault tolerance of the system has been largely restricted . Reliability of the neural network becomes more and more important , there is an urgent need to establish the theory and method of neural network analysis and design of high- reliability . This article describes the initial framework of the fault tolerance of neural network theory , fault - tolerant neural networks applied to fault diagnosis and simulation and experimental results show that such a fault tolerant neural network is able to maintain the same performance in the network failure , network failure , also has a good performance . This method greatly improves the fault diagnosis , fault tolerance .

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CLC: > Industrial Technology > Automation technology,computer technology > Automated basic theory > Artificial intelligence theory > Artificial Neural Networks and Computing
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