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Traction power supply system fault diagnosis model based on Bayesian network considering the uncertainty of information

机译:考虑信息不确定性的基于贝叶斯网络的牵引供电系统故障诊断模型

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摘要

Fault diagnosis is of great significance to maintain safe and stable operation of the traction power supply system. Fast diagnosing fault to restore power supply is important. A kind of TPSS fault diagnosis model based on Bayesian network considering the uncertainty of information is proposed in this paper. The fault diagnosis model inherits the capability of dealing with uncertain information of Bayesian network and reduces the uncertainty from original source. A fault simulation model is proposed to produce sample data for learning parameters. Accuracy of fault diagnosis model and fault simulation model are verified by an example of failure event.
机译:故障诊断对于维持牵引供电系统的安全稳定运行具有重要意义。快速诊断故障以恢复电源很重要。提出一种考虑信息不确定性的基于贝叶斯网络的TPSS故障诊断模型。故障诊断模型继承了处理贝叶斯网络不确定信息的能力,减少了原始来源的不确定性。提出了一种故障仿真模型来产生用于学习参数的样本数据。通过故障事件实例验证了故障诊断模型和故障仿真模型的准确性。

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