Research on the inspection technology of the urban public areas

Yiying Zhang, Xiaoning Hou, Hao Liu, Quanlei Wang, Huailin Liu
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Abstract

This paper develops an automatic system for the surface distress inspections on the urban public areas, including sidewalks, squares, and parking lots. This inspection system integrates an industrial 3D camera, a positioning system supporting both GNSS and Beidou, a distance measurement instrument (DMI), an inertial measurement unit (IMU), a power supply, a time synchronization technology, and a data acquisition software, such that it can collect 3D images of the surfaces of the urban public areas at a normal walking speed (~5km/hr). This inspection system has several advantages over the traditional manual inspections, such as low cost, high efficiency, low power consumption and compacted size. The field tests are conducted on the urban public areas in Nan’an District to validate the effectiveness of the inspection system. The engineering applications indicate that the inspection system works well and collects high-quality 3D images in either time mode or distance mode. The collected 3D images will be used for further analysis of the surface distress extractions, such as crack, pothole, and faulting. Finally, a basic neutral network is created to determine if there are distresses in the 3D images from field tests with the accuracy higher than 90%, which is very promising.
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城市公共区域检测技术研究
本文开发了一种城市公共区域(包括人行道、广场和停车场)地面破损自动检测系统。该检测系统集成了工业3D相机、支持GNSS和北斗的定位系统、距离测量仪(DMI)、惯性测量单元(IMU)、电源、时间同步技术和数据采集软件,可以在正常步行速度(~5km/hr)下采集城市公共区域表面的3D图像。与传统的人工检测相比,该检测系统具有成本低、效率高、功耗低、体积小等优点。在南岸区城市公共区域进行了现场试验,验证了该检测系统的有效性。工程应用表明,该检测系统在时间模式和距离模式下均能采集到高质量的三维图像。收集到的3D图像将用于进一步分析地表损伤提取,如裂缝、坑洞和断层。最后,建立了一个基本的神经网络来判断现场测试的三维图像中是否存在遇险,准确率高于90%,具有很好的应用前景。
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