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基于改进贝叶斯网络的电力设备绝缘故障诊断方法

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为保障电力系统的安全、高效运行,实现对电力设备绝缘故障的准确诊断,提高电力设备的可靠性,利用改进贝叶斯网络,提出了一种全新的绝缘故障诊断方法.首先,利用传感器进行电力设备状态信号采样;其次,利用统计特征提取方法,确定可能影响绝缘性能的特征参数,提取电力设备绝缘故障特征;再次,在此基础上,基于改进贝叶斯网络建立绝缘故障诊断模型,初步判断设备的健康状态;最后,计算各故障节点的后验概率,实现故障诊断与推理目标.实验结果表明,应用该方法进行故障诊断,具有较小的诊断误差,能够更准确地诊断电力设备的绝缘性能指标.
Modified Bayesian Networks-based Insulation Fault Diagnosis for Power Equipment
In order to ensure safe and efficient operation of power system,achieve accurate diagnosis of insulation faults,and improve the reliability of power equipment,a new insulation fault diagnosis method is proposed based on a modified Bayesian network.This methodology entails the power equipment status signal sampling by sensors,the determination of characteristic parameters and the extraction of fault characteristics by statistical feature extraction methods,the modeling of insulation fault diagnosis based on modified Bayesian networks and the preliminary identification of equipment health status,as well as calculation of the posterior probability of each faulty node to achieve fault diagnosis.The method is veri-fied by experiment to have a small diagnostic error in diagnosing and predicting the insulation performance indicators of power equipment.

modified Bayesian networkspower equipmentinsulationdiagnosis

陈林峰

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国家能源集团宿迁发电有限公司,江苏 宿迁 223800

改进贝叶斯网络 电力设备 绝缘 诊断

2024

电工技术
重庆西南信息有限公司(原科技部西南信息中心)

电工技术

影响因子:0.177
ISSN:1002-1388
年,卷(期):2024.(14)