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基于高压绝缘套管纹理特征的红外目标检测

赵洪山 张则言 孟航 张峻豪

赵洪山, 张则言, 孟航, 张峻豪. 基于高压绝缘套管纹理特征的红外目标检测[J]. 红外技术, 2021, 43(3): 258-265.
引用本文: 赵洪山, 张则言, 孟航, 张峻豪. 基于高压绝缘套管纹理特征的红外目标检测[J]. 红外技术, 2021, 43(3): 258-265.
ZHAO Hongshan, ZHANG Zeyan, MENG Hang, ZHANG Junhao. Infrared Target Detection of High Voltage Insulation Bushing Based on Textural Features[J]. Infrared Technology , 2021, 43(3): 258-265.
Citation: ZHAO Hongshan, ZHANG Zeyan, MENG Hang, ZHANG Junhao. Infrared Target Detection of High Voltage Insulation Bushing Based on Textural Features[J]. Infrared Technology , 2021, 43(3): 258-265.

基于高压绝缘套管纹理特征的红外目标检测

详细信息
    作者简介:

    赵洪山(1965-),男,汉族,河北沧州人,教授,博士生导师,研究方向为电力系统分析、运行与控制、智能配电网载波通信与自动化、电力设备故障预测与优化检修等。E-mail:zhaohshcn@126.com

  • 中图分类号: TP391.41

Infrared Target Detection of High Voltage Insulation Bushing Based on Textural Features

  • 摘要: 在基于传统图像分割法的红外图像目标检测中,当背景颜色和被检测物体颜色相近时,往往难以有效地识别红外图像中的被检测物。所以为了进一步提高绝缘套管在红外图像中的识别精度,文中提出一种基于绝缘套管伞裙纹理特征的目标检测方法。首先为增强图像纹理特性,将双边滤波代替传统高斯-拉普拉斯算子中的高斯卷积滤波,通过双边-拉普拉斯进行图像滤波和增强。之后针对高压绝缘套管外层伞裙的特殊纹理,建立反映伞裙周期性分布的描述子,并通过图像扫描法进行粗识别。最终基于DBSCAN(Density-Based Spatial Clustering of Applications with Noise)聚类算法,建立其超参数求解方法,实现离群点剔除和特征聚类,完成高压绝缘套管的精细分割。通过实验对比其他绝缘套管红外图像的识别算法,文中算法可以有效地精细分割出绝缘套管主体,克服其他图像分割方法的不足。并在数据集上识别率达到85%以上。
  • 图  1  110 kV电容式电压互感器结构图

    Figure  1.  Configuration of 110 kV capacitance type voltage transformer

    图  2  典型滤波算子对比图

    Figure  2.  Comparison of typical filtering operators

    图  3  采样直线周期性特征

    Figure  3.  Sampling line periodic characteristics

    图  4  图像扫描法的粗识别

    Figure  4.  Preliminary recognition of image scanning method

    图  5  基于DBSCAN密度聚类的离群点剔除

    Figure  5.  Outlier removal based on DBSCAN density clustering

    图  6  目标检测识别方框

    Figure  6.  Object detection recognition box

    图  7  算法分割及识别效果对比图一

    Figure  7.  Three types of algorithm segmentation and recognition effect in the first comparison chart

    图  8  算法分割及识别效果对比图二

    Figure  8.  Three types of algorithm segmentation and recognition effect in the second comparison chart

    表  1  红外图像采集设备介绍

    Table  1.   Introduction of infrared image acquisition equipment

    Parameter Value Parameter Value
    Acquisition equipment FLIR T600 Measurement accuracy ±2℃
    Wavelength 7-13 μm Resolution 240×320
    Temperature range -40℃-130℃ Measuring distance 12-15 m
    下载: 导出CSV

    表  2  测试数据检测结果

    Table  2.   Results of test data

    The algorithm of paper Reference [18] Reference [19]
    IoU 0.766 0.649 0.703
    pre 0.872 0.673 0.746
    下载: 导出CSV
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  • 收稿日期:  2020-05-26
  • 修回日期:  2020-06-29
  • 刊出日期:  2021-04-02

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