An Intelligent Identification and Acquisition System for UAVs Based on Edge Computing Using in the Transmission Line Inspection

Liu Yue, Wang Wanguo, Xu Ronghao, Li Zengwei, Tian Ran Yuan
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引用次数: 2

Abstract

With the increase of the transmission line mileage, the transmission line inspection is facing severe challenges. As an efficient inspection way, the UAV (Unnamed Aerial Vechicle) is used for the transmission line inspection. However, at the present stage, to complete the observation and data collection of transmission line equipment, the PTZ (Pan Tilt Zoom) camera in the UAV is completely controlled dependent on the operator during the inspection. These needs higher requirements for the operator and lead to high labor intensity. And the image scale of the collection device is not uniform, which improves the difficulty of subsequent intelligent diagnosis of defects. In order to solve this problem, this paper designs an intelligent acquisition system for UAVs based on edge computing using in the transmission line inspection. The system includes the front-end edge computing detection module based on SSD (Single Shot Multibox Detector) algorithm and a PTZ camera control module. The system workflow is as follows: firstly, the UAV acquires the video stream data of the surrounding environment of the transmission line through the fixed-focus camera in the PTZ. The front-end edge computing detection module receives the video stream through the USB interface. And the front-end edge computing module uses the SSD algorithm to identify the video stream gotten from the PTZ camera to recognize and locate the transmission line equipment. Secondly, if the transmission line equipment is identified in the field of view, such as an insulator, the anti-vibration hammer, the equalizing ring, etc., the front-end edge computing module calculates the target image ratio of the device and from the center position based on the identified pixel position information of the transmission line equipment, and converts to the pan-tilt rotation amount and camera pulling factor. The pan-tilt rotation amount and camera pulling factor is transmitted to the PTZ camera control module through the serial port. The PTZ camera control module controls the camera's movement until the transmission line equipment is in the center of the field of view. Finally, the wide-angle camera in dual-view PTZ camera is controlled to zoom. And the image after the zoom is photographed and saved to finish a flow of the data of transmission line equipment collects. After testing, the SSD algorithm for transmission line equipment can achieve an overall recognition accuracy of 73%. The insulator identification accuracy is 75.7%.The anti-vibration hammer identification accuracy is 72.6%.And the equalization ring recognition accuracy is 70.3%.The acquisition video is 1080P, the edge computing module processing speed is 3fp/s, and the pan/tilt control module controls the pan/tilt camera to complete a shooting time of 3s. On the one hand, the system realizes the autonomy, process and standardized collection of the image information during the transmission line equipment while improving the validity of the image data information and reduces the complexity of the subsequent defect diagnosis. On the other hand, it also reduces the manual participation degree of the inspection operation so that the efficiency can be increased by 5~7 times compared with the manual control of the PTZ camera for equipment acquisition.
基于边缘计算的无人机智能识别与采集系统在传输线检测中的应用
随着输电线路里程的增加,输电线路巡检工作面临着严峻的挑战。作为一种高效的巡检方式,无人机被用于输电线路巡检。然而,在现阶段,为了完成对传输线设备的观测和数据收集,无人机中的PTZ (Pan Tilt Zoom)摄像机在检查期间完全依赖于操作员控制。这对操作人员的要求更高,劳动强度也较高。并且采集装置的图像尺度不均匀,提高了后续智能诊断缺陷的难度。为了解决这一问题,本文设计了一种基于边缘计算的无人机智能采集系统,用于传输线检测。该系统包括基于SSD (Single Shot Multibox Detector)算法的前端边缘计算检测模块和PTZ摄像机控制模块。系统工作流程如下:首先,无人机通过PTZ内的定焦摄像头采集传输线周围环境的视频流数据。前端边缘计算检测模块通过USB接口接收视频流。前端边缘计算模块采用SSD算法对PTZ摄像机接收到的视频流进行识别,对传输线设备进行识别和定位。其次,如果在视场中识别出传输线设备,如绝缘子、防振锤、均衡环等,前端边缘计算模块根据识别出的传输线设备像素位置信息,从中心位置计算出该设备的目标图像比,并转换为平移旋转量和摄像机拉拔因子。通过串口将平移旋转量和摄像机牵引系数传输到PTZ摄像机控制模块。PTZ摄像机控制模块控制摄像机的运动,直到传输线设备位于视场中心。最后,控制双视角PTZ相机中的广角镜头变焦。并对变焦后的图像进行拍摄和保存,完成对传输线设备的数据采集流程。经过测试,该算法对传输线设备的整体识别准确率达到73%。绝缘子识别准确率为75.7%。抗振锤识别精度为72.6%。均衡环识别精度为70.3%。采集视频为1080P,边缘计算模块处理速度为3fp/s,平移/倾斜控制模块控制平移/倾斜摄像头,完成一次拍摄时间为3s。一方面,系统实现了传输线设备过程中图像信息的自主化、流程化和标准化采集,同时提高了图像数据信息的有效性,降低了后续缺陷诊断的复杂性。另一方面,它也降低了检测操作的人工参与程度,与手动控制PTZ摄像机进行设备采集相比,效率可提高5~7倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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