利用深度学习模型智能识别地下排水管道缺陷

doi:10.13474/j.cnki.11-2246.2021.322

测绘通报 ›› 2021, Vol. 0 ›› Issue (10): 141-145.doi: 10.13474/j.cnki.11-2246.2021.322

利用深度学习模型智能识别地下排水管道缺陷

王大成, 谭军辉, 彭述刚, 钟镇声, 陈国强, 李国桥

广东绘宇智能勘测科技有限公司, 广东广州 510665

收稿日期:2020-10-09 修回日期:2021-07-13 出版日期:2021-10-25 发布日期:2021-11-13
通讯作者: 彭述刚。E-mail:1933811175@qq.com
作者简介:王大成(1971-),男,高级工程师,主要从事智能测绘信息化研究。E-mail:948609547@qq.com
基金资助:
2019年珠海市促进实体经济高质量发展专项资金（珠工信〔2019〕557号）

Intelligent identification system of drainage pipelines defects based on deep learning model

WANG Dacheng, TAN Junhui, PENG Shugang, ZHONG Zhensheng, CHEN Guoqiang, LI Guoqiao

Guangdong Huiyu Intelligent Survey Technology Co., Ltd., Guangzhou 510665, China

Received:2020-10-09 Revised:2021-07-13 Online:2021-10-25 Published:2021-11-13

摘要/Abstract

摘要： 排水管道健康状况直接影响整个城市的排水效果，CCTV检测作为目前最为常见的排水管道健康状况检测方法，仍存在自动化程度不高、工作效率低下、严重依赖人工经验等问题。为解决以上问题，本文将当前先进的深度学习技术与地下排水管道缺陷检测技术相结合，提出了一种基于深度学习模型的地下排水管道缺陷智能识别技术。同时，将管道缺陷智能识别与管道检测工作流程紧密结合，实现城市排水管道检测报告的快速自动生成等功能，从而大大提高排水管道缺陷的检测效率。

关键词: 排水管道缺陷, 深度学习模型, CCTV检测, 卷积神经网络, 智能识别系统

Abstract: The health condition of the drainage pipeline directly affects the drainage effect of the whole city. In order to find the hidden danger of the drainage pipeline, it is necessary to detect the internal defects of the pipeline in time. CCTV detection technology is currently the most common pipeline defect method, but there are some problems such as low automation degree, low work efficiency and heavy reliance on manual experience. To solve these problems, this paper combines the deep learning technology with the detection technology of drainage pipeline, and put forward an intelligent identification technology of drainage pipelines defects based on deep learning model. Meanwhile, the intelligent identification of pipeline defects and pipeline detection workflow are closely combined to realize the rapid and automatic generation of drainage pipeline detection report, thus greatly improving the detection efficiency of drainage pipeline defects.

Key words: drainage pipelines defect, deep learning model, CCTV detection, convolutional neural network, intelligent identification system

中图分类号:

P208

王大成, 谭军辉, 彭述刚, 钟镇声, 陈国强, 李国桥. 利用深度学习模型智能识别地下排水管道缺陷[J]. 测绘通报, 2021, 0(10): 141-145.

WANG Dacheng, TAN Junhui, PENG Shugang, ZHONG Zhensheng, CHEN Guoqiang, LI Guoqiao. Intelligent identification system of drainage pipelines defects based on deep learning model[J]. Bulletin of Surveying and Mapping, 2021, 0(10): 141-145.

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利用深度学习模型智能识别地下排水管道缺陷

Intelligent identification system of drainage pipelines defects based on deep learning model

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