摘要
本文针对电力设备红外图像诊断中热故障特征提取和数字化表达难题,提出一种多属性融合的电力设备红外热特征数字化方法。通过对电力设备热故障特性和相关诊断文件研究分析,在对图像预处理的基础上,提取图像中关键发热区域的热点温度、热点温差、发热面积、位置信息以及热点群聚现象等热属性值,构建多属性信息融合的过热性故障特征值向量,实现热故障特征数字化描述。以断路器为例对该方法进行了验证分析,结果表明,该方法对典型红外故障图谱具有良好的描述能力,可用于后续大量复杂故障样本情况下的设备热故障智能分类与诊断应用中。
Aiming at the complex problem of thermal fault feature extraction and digital representation in the infrared image diagnosis of power equipment,a multi-attribute fusion thermal feature digitization method for power equipment is proposed in this study.The method uses heat power equipment fault features and diagnostic files related to research analysis,based on image preprocessing,to extract the images of key areas with high temperatures,heating area,location,and thermal property values,such as hot clustering,building a multiple-attribute information fusion of overheating fault feature vectors to realize a digital description of the thermal fault characteristics.A circuit breaker is used as an example to verify and analyze the proposed method.The results show that the proposed method can effectively describe the typical infrared fault spectrum,and can be used in the intelligent classification and diagnosis of equipment faults in the case of a large number of complex fault samples.
作者
赵天成
罗吕
杨代勇
刘赫
袁刚
许志浩
ZHAO Tiancheng;LUO Lyu;YANG Daiyong;LIU He;YUAN Gang;XU Zhihao(Electric Power Science Research Institute of State Grid Jilin Electric Power Co.,LTD.,Changchun 130021,China;College of Electrical Engineering,Nanchang University of Engineering,Nanchang 330099,China)
出处
《红外技术》
CSCD
北大核心
2021年第11期1097-1103,共7页
Infrared Technology
基金
吉林省电力科学研究院有限公司科技项目资助(KY-GS-20-01-07)。
关键词
多属性融合
特征提取
特征向量
数字化描述
multi-attribute fusion
feature extraction
eigen vector
digital description
作者简介
赵天成(1992-),男,吉林长春人,工程师,硕士,研究方向为电力设备故障检测与诊断。E-mail:583107503@qq.com;通信作者:许志浩(1988-),男,武汉人,讲师,博士,硕导,研究方向为电力设备智能检测与人工智能应用。E-mail:zhxuhi@whu.edu.cn。
