燕山大学学报2016，Vol.40Issue(4)：336-341,6.DOI:10.3969/j.issn.1007-791X.2016.04.007
T-S模糊神经网络在风机故障诊断中的应用
Application of T-S fuzzy neural network in fault diagnosis of ventilator
摘要
Abstract
Aiming at the ventilator faults with uncertainty and complexity characteristics in heating boiler house, combining the a-daptive and learning capabilities of neural network and the language description to get knowledge of fuzzy system, a two stage fault diagnosis model of ventilator based on T-S fuzzy neural network is proposed, which can diagnose the types of faults and identify the causes of faults, according to the changes in the characteristics spectrum values of the vibration signal of common faults. With the simulation tests by MATLAB software, through the example comparison of the fuzzy neural network and the BP neural network, the results illustrate that the fault diagnosis method of the fuzzy neural network can recognize the faults rapidly, accurately and steadily, which provides a efficient way for the diagnosis.关键词
风机/模糊神经网络/BP神经网络/故障诊断Key words
ventilator/fuzzy neural network/BP neural network/fault diagnosis分类
建筑与水利引用本文复制引用
张昭,李风雷,田琦..T-S模糊神经网络在风机故障诊断中的应用[J].燕山大学学报,2016,40(4):336-341,6.基金项目
国家“十二五”科技支撑计划项目 （）
