基于AIA-ELM模型的继电保护设备监测方法设计

Design of Monitoring Method for Relay Protection Equipment Based on AIA- ELM Model

  • 摘要: 计。设计了继电保护设备状态在线监测架构,采集设备状态信息;通过分层融合方法整合、解析并存储了数据采集层获取 设备状态数据,利用分形维数判断设备状态,对故障信号特征进行提取;采用免疫算法优化了极限学习机线性参数与输入 权值、隐含层节点阈值,提高了泛化性能,构建了基于AIA-ELM模型,对设备故障信号进行故障识别与诊断,实现设备监测。 经过对比试验验证了该方法能够提高继电保护设备的监测准确率至96.5%以上,降低了信号误差,可有效保障电力系统的 运行安全。

     

    Abstract: design of relay protection equipment monitoring method based on AIA-ELM model is proposed. The online monitoring architecture of relay protection equipment status is designed to collect equipment status information;Through the hierarchical fusion method, the data acquisition layer is integrated,analyzed and stored to obtain the equipment status data. The fractal dimension is used to judge the equipment status,and the fault signal features are extracted;The immune algorithm is used to optimize the linear parameters and input weights of the limit learning machine, the hidden layer node threshold,and improve the generalization performance. Based on the AIA-ELM model,the equipment fault signal is identified and diagnosed to achieve equipment monitoring. The comparison experiment shows that the method can improve the monitoring accuracy of relay protection equipment to more than 96.5%,reduce the signal error,and effectively ensure the operation safety of power system.

     

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