Research on Electronic Equipment Fault Diagnosis Based on Improved BP Algorithm

Dong-Sheng Xu
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Abstract

It is increasingly difficult for the traditional fault diagnosis technologies to meet the complex and automation requirements of electronic equipments, so the combination of artificial intelligence technology has become a development direction of fault diagnosis. In the fault diagnosis, BP neural network has also been widely used. As for the deficiency of BP network, the paper presented an improved BP network dynamic parameter adjust algorithm and applied it in the research of electronic equipment fault diagnosis. Proved theoretically and practically, the method can effectively overcome the deficiency of standard BP algorithm, and provides efficient way for the fault diagnosis of electronic equipments
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基于改进BP算法的电子设备故障诊断研究
传统的故障诊断技术越来越难以满足电子设备复杂、自动化的要求,因此人工智能技术的结合已成为故障诊断的发展方向。在故障诊断中,BP神经网络也得到了广泛的应用。针对BP网络的不足,提出了一种改进的BP网络动态参数调整算法,并将其应用于电子设备故障诊断的研究中。理论和实践证明,该方法能有效克服标准BP算法的不足,为电子设备的故障诊断提供了有效的方法
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