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文中将神经网络技术运用于滚动轴承故障诊断．着重讨论了传统故障诊断技术所面临的挑战及基于神经网络的故障诊断技术的优越性．传统的故障诊断专家系统在知识的获取及表达上存在着困难，并且当系统较大时，变得非常庞大，不适于在线控制；人工神经网络对信息分布式的存储及处理，具有明显的优点．以滚动轴承故障诊断为例，编制了基于神经网络技术的诊断程序，运行结果表明，该方法具有判断准确、容错性好、适于在线工作、便于推广的优点．
In this paper, neural network technology is applied to fault diagnosis of rolling bearing. This paper focuses on the challenges of traditional fault diagnosis technology and the superiority of fault diagnosis technology based on neural network. The traditional fault diagnosis expert system has difficulty in obtaining and expressing knowledge, and becomes very large when the system is large, which is not suitable for online control. The artificial neural network has obvious advantages for information distributed storage and processing . Taking the fault diagnosis of rolling bearing as an example, a diagnostic program based on neural network technology is compiled. The running results show that the method has the advantages of accurate judgment, good fault tolerance, suitable for online work and easy popularization.