摘要
针对当前水下巡检工作面临的诸多挑战,如水下环境复杂多变、传统巡检方式效率低下且存在安全隐患,深入研究水工建筑物水下巡检及检测作业平台,该平台由硬件层、网络层、数据层、服务层和应用层构成。首先,硬件层利用先进水下机器人,采集水工建筑物周边水质信息及水下图像或视频等关键数据。其次,网络层保证数据传输的实时性和稳定性,并将数据存储至数据层。再次,服务层将数据传输至软件处理系统,并结合卷积神经网络等人工智能技术,实现水工建筑物缺陷检测与水下机器人巡检路线规划。最后,应用层提供电脑端浏览器接口与微信服务号接口,用户可以直观地查看巡检与检测结果。实验结果显示,该平台可准确监测水工建筑物周边水质信息,提供清晰的水下图像和视频资料,获取高精度的水工建筑物缺陷检测结果。
Aiming at the numerous challenges the current underwater inspection work facing,such as the complexity and variability of the underwater environment,the inefficiency of the traditional inspection methods and the existence of safety hazards,an underwater inspection and detection platform for hydraulic structures is thoroughly studied.This platform consists of a hardware layer,a network layer,a data layer,a service layer and an application layer.Firstly,the hardware layer utilizes advanced underwater robots to collect critical data such as water quality information around the hydraulic structures,as well as underwater images or videos.Secondly,the network layer ensures real-time and stable data transmission,with the data being stored in the data layer.Thirdly,the service layer transmits the data to a software processing system and combines artificial intelligence technologies such as convolutional neural networks to achieve defect detection in hydraulic structures and route planning for underwater robots.Finally,the application layer provides interfaces for computer browsers and WeChat service accounts,allowing users to view the inspection and detection results visually.Experimental results show that the platform can accurately monitor water quality information around hydraulic structures,provide clear underwater images and video materials,and obtain high-precision defect detection results for hydraulic structures.
作者
莫剑
张振
张军
张弘强
MO Jian;ZHANG Zhen;ZHANG Jun;ZHANG Hongqiang(State Grid Hunan Electric Power Company Limited,Changsha 410004,China;State Grid Hunan Electric Power Company Limited Research institute,Changsha 410208,China;State Grid Hunan Electric Power Company Limited Hydropower Branch,Changsha 410029,China)
出处
《湖南电力》
2025年第3期141-146,共6页
Hunan Electric Power
基金
国网湖南省电力有限公司科技项目(5216A5220020)。
关键词
水工建筑物
水下巡检
检测作业平台
水下机器人
缺陷检测
hydraulic structures
underwater inspection
detection operation platform
underwater robots
defect detection
