Equipment fault diagnosis method based on case reasoning

The invention discloses an equipment fault diagnosis method based on case reasoning, which comprises the following steps: acquiring historical fault case data of equipment, and establishing a fault case library according to the historical fault case data; training the RBF neural network by adopting case data in the fault case library; performing feature extraction and vectorization on a to-be-diagnosed fault, and inputting the to-be-diagnosed fault into the trained RBF neural network for retrieval reasoning; and selecting fault cases with high similarity, determining corresponding fault reasons and solutions according to the fault cases, and updating the fault case library. According to the equipment maintenance system, intelligent query, case accumulation and fault reasoning can be realized, so that the rapid fault detection and diagnosis capability of equipment is improved. 本发明公开了一种基于案例推理的装备故障诊断方法，包括获取装备的历史故障案例数据，据此建立故障案例库；采用故障案例库中的案例数据对RBF神经网络进行训练；对待诊断故障进行特征提取和向量化后输入训练好的RBF神经网络进行检索推理；选取相似度高的故障案例，据此确定对应故障原因