高压充油电缆终端的可靠运行是电缆线路稳定运行的前提,但传统充油电缆终端故障诊断模型存在效率低、可靠性差等问题.为准确判断充油电缆终端故障,提出一种最大互信息系数(maximal information coefficient,MIC)结合改进阿基米德算法(improved Archimedes optimization algorithm,IAOA)优化深度置信网络(deep belief network,DBN)的充油电缆终端故障诊断方法.首先,采用MIC理论对电缆终端用硅油中溶解气体浓度的特征量进行降维处理并提取特征量;其次,将优选的特征量作为DBN网络模型的输入,并针对DBN网络超参数选取困难的缺点,提出采用IAOA优化DBN网络模型的超参数;再者,针对AOA算法容易陷入局部最优和搜索能力差等不足,引入多种改进策略优化AOA的方法提高AOA的寻优能力.最后,通过搭建充油电缆终端故障模拟实验平台,收集充油电缆终端故障样本数据并创建类别样本标签,验证了该模型的可行性.实例表明,所提出的诊断方法可以较好地完成故障诊断,测试集的准确率为98.33％.与传统故障诊断模型相比,该方法稳定性好、识别精度高,可为保障高压充油电缆终端的可靠运行提供理论基础.
Fault Diagnosis Method for Oil Filled Cable Terminals Based on MIC and IAOA-DBN
The reliable operation of high-voltage oil-filled cable terminals is a prerequisite for the stable operation of cable lines,but the traditional diagnosis model for oil-filled cable terminal faults has problems such as low efficiency and poor reliability.In order to accurately judge oil-filled cable terminal faults,this paper proposes a fault diagnosis method for oil filled cable terminals based on the maximum mutual information coefficient(MIC)and the improved Archimedes opti-mization algorithm(IAOA)to optimize the deep trust network(DBN).Firstly,the MIC theory is used to reduce the dimensionality of the dissolved gas concentration in the silicone oil filling agent for cable terminals and perform feature extraction.Secondly,the optimal feature quantity is taken as the input of the DBN network model,and in view of the dif-ficulty in selecting the hyperparameter of the DBN network,the IAOA is proposed to optimize the hyperparameter of the DBN network model.It is easy for the AOA algorithm to fall into local optimization and weak search ability,thus a varie-ty of improvement strategies are introduced to optimize the optimization performance of the AOA method and improve the optimization ability of the AOA.Finally,the feasibility of the model was verified by constructing experimental plat-form for simulation of oil filled cable terminal faults,collecting fault sample data of oil filled cable terminals,and creating category sample labels.The example verification shows that the oil filled cable fault diagnosis method proposed in this paper can be adopted to effectively complete fault diagnosis,with an accuracy of 98.33％in the test set.Compared with traditional fault diagnosis models,the proposed method has good stability and high recognition accuracy,which can pro-vide a theoretical basis for guaranteeing the reliable operation of high-voltage oil filled cable terminals.
万方数据
维普
