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本文提出了一种新的基于规则和神经网络集成的智能旋转机械故障诊断方法，该法把专家经验和故障样本以统一的分布表示形式组织到知识库中，并在此基础上提出了推理算法的自学习选取。整个系统充分发挥了规则系统和神经网络的优点，具有知识表示明确、并行推理、联想和自学习等优点，最后结合实例进行了分析。
In this paper, a new fault diagnosis method of intelligent rotating machinery based on rule and neural network integration is proposed. This method organizes expert experience and fault samples into a unified distribution representation into the knowledge base, and on this basis proposes the reasoning algorithm Self-learning selection. The whole system gives full play to the advantages of the rule system and the neural network, with the advantages of clear knowledge representation, parallel reasoning, association and self-learning, and finally analyzes with examples.