基于热成像的渗漏源检测  

Leakage Source Detection Based on Thermal Imaging

作　　者：杨羽 贺超广 涂圆 赵杰锋 周晓萍[1,2] 唐立军 YANG Yu;HE Chaoguang;TU Yuan;ZHAO Jiefeng;ZHOU Xiaoping;TANG Lijun(Changsha University of Science and Technology,School of Physics and Electronic Science,Changsha 410114,China;Key Laboratory of Electromagnetic Environment Monitoring and Modeling in Hunan Province,Changsha 410114,China)

机构地区：[1]长沙理工大学物理与电子科学学院,湖南长沙410114 [2]近地空间电磁环境监测与建模湖南省普通高校重点实验室,湖南长沙410114

出　　处：《红外技术》2022年第7期750-756,共7页Infrared Technology

基　　金：国家级大学生创业实践项目(S201910536003S);湖南省重点研发计划项目(2018GK2054)。

摘　　要：针对屋面渗漏源难以检测的问题,研究了基于渗漏区域红外图像特征的灰度分段映射图像增强方法,提出了一种基于样板矩阵的图像快速识别技术,设计了一个屋面全自动渗漏源检测系统。在5m×3 m屋面设置渗漏源形成多个渗漏区域,采用Mecanum轮小车搭载该系统对渗漏源进行检测,结果表明,该系统可以在89 s之内完成检测工作,总测试150个次渗漏点,漏测12个次渗漏点,识别准确率大于90%。该技术检测效率高、操作简单,配合相应载体可用于各类不明渗水源检测。To address the difficulty in detecting the source of roof leakage, an image enhancement method that uses the infrared image features of the leakage area was studied using gray segmentation mapping. Rapid image recognition technology based on a template matrix was proposed, and an automatic roof leakage source detection system was designed. Leakage sources were set on a 5 m× 3 m roof to form multiple leakage areas.A mecanum wheeled trolley was used to support the system while detecting these sources. The results showed that the system could complete detection within 89 s, with a total of 150 leakage points tested and 12 leakage points missed, and the identification accuracy was greater than 90%. This technology has high detection efficiency and simple operation and can be used to detect all types of unknown water seepage sources with the corresponding carrier.

关 键 词：红外热成像 渗漏源检测 图像识别 灰度分段 

分 类 号：TN219[电子电信—物理电子学]