基于模糊神经网络的通风机故障诊断系统

Fault Diagnosis System of Ventilator Based on Fuzzy Neural Network

针对矿用通风机故障具有不确定性和复杂性的问题,利用风机的振动参数进行推理,提取常见故障振动信号的特征频谱值来组建及训练神经网络,以此建立诊断系统进行故障类型的识别。诊断结果与实际故障相符,表明基于模糊神经网络故障诊断方法能够快速准确地得到风机故障的特征和状态,增加了风机故障诊断的可靠性和实用性。

Aiming at the mine ventilator determine fault with uncertainty and complexity problem,for mine fan put forward a kind of fault diagnosis based on fuzzy neural network fault diagnosis expert system for mine ventilator.Extraction of the common faults the vibration signal characteristics spectrum values to training of network.And with a fault of the fan for verification examples,and the results show that the system diagnostic efficiency,high accuracy,for mine fan of fault diagnosis for a new diagnostic method