电器与能效管理技术Issue(2)：56-65,10.DOI:10.16628/j.cnki.2095-8188.2024.02.010
基于卷积原型网络的断路器故障诊断方法研究
Research on Fault Diagnosis Method of High Voltage Circuit Breaker Based on Convolution Prototype Network
摘要
Abstract
Aiming at the problem that unknown samples cannot be effectively distinguished in existing circuit breaker fault diagnosis research,a circuit breaker fault diagnosis algorithm based on the convolutional prototype network is proposed.Firstly,the classification function is constructed using the clustering approach and the probability space is divided based on the distance constraint of the prototype sample point feature space for various types of faults,which can achieve the recognition of a sample set containing unknown fault classes.At the same time,with each type of prototype sample points as the cluster center,the sample feature space distance is used as the optimization target of the convolution feature self-extraction network,which can effectively improve the intra-class aggregation and inter-class dispersion of fault sample features and improve the classification accuracy of the model.Finally,the validity and accuracy of the proposed algorithm are verified based on the field experiment data of 110 kV circuit breaker.The results show that the proposed algorithm can accurately distinguish the unknown faults in the test samples and effectively improve the spatial distribution of fault sample features.关键词
断路器/故障诊断/原型卷积网络/聚类/未知类/智能运维Key words
circuit breaker/fault diagnosis/prototype convolutional network/clustering/unknown class/intelligent maintenance分类
信息技术与安全科学引用本文复制引用
沙浩源,刘佩,王之赫,孙毅,赵贺,邓凯,朱超..基于卷积原型网络的断路器故障诊断方法研究[J].电器与能效管理技术,2024,(2):56-65,10.基金项目
国家重点研究计划项目(2018YFB1500800) （2018YFB1500800）
江苏省重点研发计划(BE2020027) （BE2020027）
江苏省国际科技合作项目(BZ2021012) （BZ2021012）
