Infrared Image Segmentation and Temperature Reading of Composite Insulator Strings Based on Mask-RCNN Algorithm

HUANG Xinyu; ZHANG Yang; WANG Liming; MEI Hongwei; ZHANG Zhonghao; WEN Lu

doi:10.13296/j.1001-1609.hva.2021.09.012

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Infrared Image Segmentation and Temperature Reading of Composite Insulator Strings Based on Mask-RCNN Algorithm

更新时间：2025-04-26

- Infrared Image Segmentation and Temperature Reading of Composite Insulator Strings Based on Mask-RCNN Algorithm
- High VoltageApparatus Vol. 57, Issue 9, Pages: 87-94(2021)
- 作者机构：
  
  1. 清华大学深圳研究生院
  2. 山东电力科学研究院
- 作者简介：
- 基金信息：
- DOI：10.13296/j.1001-1609.hva.2021.09.012
  CLC： TM216;TN219;TP391.41
- Published：2021
- 稿件说明：
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HUANG Xinyu, ZHANG Yang, WANG Liming, et al. Infrared Image Segmentation and Temperature Reading of Composite Insulator Strings Based on Mask-RCNN Algorithm[J]. High voltageapparatus, 2021, 57(9): 87-94.
DOI：

HUANG Xinyu, ZHANG Yang, WANG Liming, et al. Infrared Image Segmentation and Temperature Reading of Composite Insulator Strings Based on Mask-RCNN Algorithm[J]. High voltageapparatus, 2021, 57(9): 87-94. DOI： 10.13296/j.1001-1609.hva.2021.09.012.

摘要

红外成像可以快速发现复合绝缘子异常温升

从而实现缺陷检测。为了解决复合绝缘子红外检测中人工诊断时间成本高、效率低、背景干扰多的问题

文中提出了基于Mask-RCNN的温升绝缘子自动检测方法。首先使用Mask-RCNN对红外图像数据进行学习训练

进而对其中的绝缘子目标进行识别检测和图像分割。在智能分割之后

通过识别图中的温度范围数据并将绝缘子区域图像灰度与之比对

得到了绝缘子的温度信息

用于绝缘子异常发热故障的诊断。实验研究表明:在对南方某市绝缘子红外测温图像的自动识别中

Mask-RCNN有着优异的表现

能够运用于在巡线工作中

可以有效减轻人工处理数据的压力

对于提升推进智能巡线的智能化水平、保障输电线路安全运行有着重要的意义。

Abstract

Infrared images can find the abnormal temperature rise of the composite insulator quickly

thus achieving defect detection. For solving such problems in the infrared detection of the composite insulator as high cost

low efficiency and many backgrounds interference in the artificial diagnosis

an automatic detection method for temperature rise of insulator based on mask regional convolutional neural network（Mask-RCNN）is proposed in this paper. Firstly

the infrared image data is learnt and trained by the use of Mask-RCNN model. And then

identification detection and image segmentation for the insulator target are performed. After the intelligent segmentation

the temperature information of the insulator is obtained by way of identifying temperature range data in the image and comparing it with the area image gray level

which is used to diagnose the abnormal heating of the insulator. The experimental study shows that in the automatic identification of the infrared temperature image for insulator in one city in the south part of China

the Mask-RCNN shows superior performance. It can be used in line patrol work

can reduce effectively the pressure of artificial processing data and has important significance in improving the intelligent level of intelligent lien patrol and assuring safe operation of transmission line.

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