J4 ›› 2009, Vol. 27 ›› Issue (03): 319-.
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张 杰a,高宪军a,姚劲勃b,张 卓a
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作者简介:
ZHANG Jiea, GAO Xian-juna, YAO Jin-bob,ZHANG Zhuoa
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摘要:
针对传统的故障诊断方法对复杂系统或装备进行故障诊断速度慢、对多故障同时发生的情况难以准确定位的问题,提出将神经网络与专家系统相融合的设计方案,建立一种基于人工神经网络的故障诊断专家系统。该专家系统结合神经网络和专家系统的优点,具有很强的自学习能力和自适应能力,可从外部环境不断吸取信息,在学习过程中不断完善自己,具有很强的容错性,善于联想、类比和推理。理论分析与仿真实验证明,该系统能实现对故障的快速准确定位,为保障装备可靠高效地发挥功能提供了有效方法
关键词: 故障诊断, 神经网络, 专家系统
Abstract:
The traditional fault diagnosis methods have the shortcomings that the diagnosis speed is slow and it was hard to accurately fix the faults taking place at one time when it is diagnosing the complicated system or equipment,a design which mixes the expert system and neural network together is proposed, and a fault diagnosis expert system is established based on artificial neural network. The high-speed diagnosis for faults taking place is realized by theoretical analysis and emulation experiment, and the results show that this fault diagnosis method is effective to solve the issue, and provides an effective amelioration method for keeping equipment reliable and efficient displaying functions.
Key words: fault diagnosis, neural network, expert system
中图分类号:
张 杰,高宪军,姚劲勃,张 卓. 基于神经网络与专家系统的故障诊断技术[J]. J4, 2009, 27(03): 319-.
ZHANG Jie, GAO Xian-jun, YAO Jin-bo,ZHANG Zhuo. Technology of Expert System Based on Neural Network[J]. J4, 2009, 27(03): 319-.
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http://xuebao.jlu.edu.cn/xxb/CN/Y2009/V27/I03/319
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