摘要
为解决现有基于红外图像识别变压器套管油位存在的过于依赖温度信息、人工处理效率低下等问题,文中结合目标检测技术提出了一种基于改进单次检测器(SSD)的套管智能油位识别方法。通过引入SSD目标检测方法,检测红外图像中的套管区域,加入损失函数以改进SSD算法从而提高套管检测准确率,并进一步通过简单线性迭代聚类(SLIC)的应用实现了不依赖红外图像温度信息的油位检测。对比文中提出的基于红外图像的油位识别算法检测结果与人工油位检测结果,表明文中提出的算法不仅在效率上领先于传统的温度检测方式,且其误差较小,仅为0.08%。对比结果验证了所提算法在保证检测精度的情况下可大幅度提高检测效率,有效提升套管故障诊断效率和智能化水平。
Recognition of transformer bushing oil level based on infrared image suffers from over-reliance on temperature information and low efficiency on manual processing.In order to solve the existing problems,an intelligent bushing oil level recognition method based on improved single shot detection(SSD)with the combination of target detection technique is proposed in this paper.The bushing area in the infrared image is detected through introducing the SSD target algorithm.And SSD algorithm is improved by adding the center loss function.Furthermore,oil level detection of bushing is achieved through the application of simple linear iterative clustering(SLIC)without relying on the temperature information.Comparative results among the image-based oil level recognition algorithm proposed in the paper and the manual oil level detection method,show that the efficiency of the proposed one is prior to that of the traditional temperature-based method.Moreover,the relative error of the algorithm is only 0.08%.Therefore,the proposed algorithm greatly improves the detection efficiency while ensuring the detection accuracy,so as to enhance the efficiency of bushing fault diagnosis and the degree of intelligence.
作者
别一凡
李波
江军
张潮海
BIE Yifan;LI Bo;JIANG Jun;ZHANG Chaohai(Jiangsu Key Laboratory of New Energy Generation and Power Conversion(Nanjing University of Aeronautics and Astronautics),Nanjing 211106,China)
出处
《电力工程技术》
北大核心
2021年第5期158-163,共6页
Electric Power Engineering Technology
基金
江苏省自然科学基金资助项目(SBK2021020744)。
关键词
变压器套管
红外图像
目标检测
损失函数
油位识别
故障诊断
transformer bushing
infrared image
object detection
loss function
oil level detection
fault diagnosis
