神经网络联想记忆模型(BAM)是近年来研究智能专家系统的一个热点。由于BAM能够存储作为变元概念的客体之间的因果关系,具有很强的处理不精确的、矛盾的、甚至是错误的数据的能力,因此将它应用到机械设备的故障诊断领域,能大大提高故障诊断的智能水平、实时处理能力及橹棒性。借助BAM模型,本文提出了一种新的故障诊断的方法。 Neural Network Associative Memory Model (BAM) is a hot spot to study intelligent expert system in recent years. Because BAM can store the causal relationship between objects as a concept of variables and has strong ability to deal with inaccurate, contradictory or even wrong data, it can be applied to the field of mechanical equipment fault diagnosis greatly Improve the intelligence level of fault diagnosis, real-time processing capability and excellent performance. With BAM model, this paper presents a new fault diagnosis method.