随后以故障树风险分析理论为基础，对故障事件进行建模和定性定量分析，确定表征设备故障特征的信息，提取关键因素。
Furthermore, fault events are modeled and made into analysis based on the risk analysis theory of fault tree. After that equipment failure characters are confirmed and key factors are exacted.
电力设备的故障诊断可以看成一个模式分类问题，每一个电力设备故障对应一组特征集。
The fault diagnosis of power equipment can be looked as pattern classification problem. Each fault of power equipment is corresponding to a set of traits.
多层前馈人工神经网络在装备故障诊断中的应用含设备运行状态特征值设定和故障判定。
The application of multi-layer feed-forward artificial neural network in fault equipment diagnosis includes feature value setting of equipment operation condition and fault judgment.
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