设备故障诊断中神经网络与证据推理结合的信息融合方法

Information Fusion of Neural Networks and Evidence Theory in Fault Diagnosis of Equipments

针对设备故障诊断中存在的处理数据量大、故障类型复杂多变、领域知识难于准确获得、故障识别率低的现状,提出了利用信息融合的思想,将神经网络和证据理论相结合应用于故障诊断的新方法。提高了故障诊断系统的灵活性、故障诊断的效率和准确性。

In fault diagnosis of equipments,problems will appear,such as:lots of data to be processed various faults,difficulty of obtaining knowledge,and low ratio of identifying faults.Information fusion is presented to sovle the above problems.Neural networks and evidence theory are combined to diagnose faults,which improves the agility,efficiency and accuracy of the fault diagnosis.