电缆终端红外图像过热区域提取方法
DOI:
作者:
作者单位:

1.国网湖北省电力有限公司武汉供电公司;2.武汉大学 电气与自动化学院

作者简介:

通讯作者:

基金项目:

国网湖北省电力有限公司科技项目(SGHBWH00YJJS2001955)


Extraction of Overheating Regions in Infrared Images of Cable Terminations
Author:
Affiliation:

1.State Grid Hubei Electric Power Company,Wuhan Power Supply Company;2.School of Electrical Engineering and Automation, Wuhan University

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
    摘要:

    红外图像中异常发热区域的准确提取,是实现电气设备热状态智能诊断的重要前提。针对电缆终端,文章提出一种红外图像过热区域提取方法。首先,利用基于最大后验概率估计的自适应小波阈值去噪方法滤除噪声,改善图像质量;之后,通过深度学习网络在图像中识别并定位出电缆终端,滤除干扰信息;最后,利用均值漂移算法实现像素点聚类,基于聚类结果提取出异常发热区域。以巡检拍摄的电缆终端红外图像作为测试样本,结果表明该方法适用于不同拍摄背景以及不同拍摄角度的红外图像,在识别并定位出电缆终端之后,能够准确提取其过热区域。且相较于现有的一些方法,文中的方法效率和准确率均更高。

    Abstract:

    Extraction of abnormal heating regions from infrared images is the important prerequisite for intelligence diagnosis of thermal state of electrical equipment. Aiming at cable terminations, an automatic extraction method is proposed in this paper. Firstly, an adaptive wavelet threshold denoising method based on Maximum a Posteriori Estimation (MAP) is applied to remove noise and improve the quality of infrared images. Then, to eliminate the interference, the deep learning network is used to identify and locate the cable terminations in the images. Finally, the Mean-Shift algorithm is applied to cluster the pixels of cable terminations, and extract the abnormal heating regions. Case studies given in this paper show that the proposed method is suitable for infrared images under different backgrounds and different angles. After identifying and locating the cable terminations, the overheating regions can be extracted accurately. Compared with some existing methods, the proposed method has better performance in efficiency and accuracy.

    参考文献
    相似文献
    引证文献
引用本文
分享
文章指标
  • 点击次数:
  • 下载次数:
历史
  • 收稿日期:2021-03-22
  • 最后修改日期:2021-05-10
  • 录用日期:2021-05-19
  • 在线发布日期: