|本期目录/Table of Contents|

[1]张卫峰,惠俊军.智能故障诊断技术的现状及展望[J].工业仪表与自动化装置,2017,(05):21-24.
　ZHANG Weifeng,HUI Junjun.The present situation and prospects of intelligence fault diagnosis technology[J].Industrial Instrumentation & Automation,2017,(05):21-24.
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智能故障诊断技术的现状及展望

《工业仪表与自动化装置》[ISSN:1000-0682/CN:61-1121/TH]

卷:
期数:
2017年05期
页码:
21-24
栏目:
出版日期:
2017-10-15

文章信息/Info

Title:
The present situation and prospects of intelligence fault diagnosis technology
作者:
张卫峰1; 惠俊军2
1.兰州工业学院 土木工程学院，兰州730050；2.陕西省宝鸡市150信箱11分箱，陕西 宝鸡721013
Author(s):
ZHANG Weifeng1;  HUI Junjun2
1.Lanzhou Institute of Technology, Lanzhou 730050,China；2.Mailbox 150 extension 11, Shaanxi Baoji 21013, China
关键词:
故障诊断; 专家系统; 神经网络; 信息融合
Keywords:
fault diagnosis;  expert system;  neural network;  information fusion
分类号:
TP206+.3
DOI:
-
文献标志码:
A
摘要:
智能故障诊断技术的发展为复杂系统的可靠性、安全性以及故障诊断提供了新的途径，它是故障诊断的高级阶段。从基于检测手段、基于知识和基于信号处理三个方面，对智能故障诊断技术做了详细的分析与探讨，并提出了未来发展方向。
Abstract:
-

参考文献/References:

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[5] 雷亚国,何正嘉.混合智能故障诊断与预示技术的应用进展[J].振动与冲击,2011(09):
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备注/Memo

备注/Memo:
收稿日期：2016-11-23作者简介：张卫峰（1977），男，硕士，讲师，研究方向为自动控制，智能控制
更新日期/Last Update: 2017-10-01