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基于多传感器信息融合的矿井通风机故障诊断
引用本文:凌六一,黄友锐. 基于多传感器信息融合的矿井通风机故障诊断[J]. 煤炭科学技术, 2008, 36(6)
作者姓名:凌六一  黄友锐
作者单位:安徽理工大学,电气与信息工程学院,安徽,淮南,232001
摘    要:为了提高矿井通风机机械故障诊断的准确性,提出了将多传感器信息融合技术用于故障诊断的检测方法.由多个传感器采集振动信号,经小波变换预处理后获得故障特征值,再经BP神经网络进行故障局部诊断,获得彼此独立的多个证据,然后运用D-S证据理论对各证据进行融合,实现对矿井通风机机械故障的准确诊断.

关 键 词:矿井通风机  故障诊断  信息融合  BP神经网络  证据理论

Fault diagnosis of mine ventilator base on multi sensor information integration
LING Liu-yi,HUANG You-rui. Fault diagnosis of mine ventilator base on multi sensor information integration[J]. Coal Science and Technology, 2008, 36(6)
Authors:LING Liu-yi  HUANG You-rui
Affiliation:LING Liu-yi,HUANG You-rui(School of Electric , Information Engineering,Anhui University of Science , Technology,Huainan 232001,China)
Abstract:In order to improve the accuracy of the fault diagnosis on mine ventilator,the paper provided the multi sensor information integration technology applied to the inspection method of the fault diagnosis.The vibration signal collected with multi sensors would be pre-treated with wavelet transformer and the fault feature values would be obtained.Then after the fault local diagnosis with the BP nervus network,several independent evidences would be acquired.Finally,each evidence would be integrated with D-S evid...
Keywords:mine ventilator  fault diagnosis  information integration  BP nervous network  evidence theory  
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