基于四旋翼无人机的桥梁裂缝检测系统设计

为解决高墩大跨桥梁裂缝检测困难的问题, 设计了四旋翼无人机桥梁裂缝检测系统, 包括无人机系统、摄像系统、数字图像处理系统。通过对桥梁检测特性及无人机动力特征的分析, 以STM32F427为主控板搭建满足飞行动力、控制、安全要求的硬件平台。在摄像系统中, 借助相机矫正提高图像精度, 采用像素物理尺寸标定、物距测量的方法, 为裂缝图像自动测量提供辅助信息, 并设计一种图像实时远程传输方案。在数字图像处理中, 针对桥梁裂缝的噪声特点, 经由中值滤波、边缘强化、阈值分割、形态学处理等获得裂缝二值图像, 结合框选法实现裂缝宽度自动测量。所设计的无人机桥梁检测系统为解决高墩大跨桥梁裂缝检测困难的问题提供了一种可行方案, 也为提高桥梁检测效率和精度提供了技术支持。

Design of quadrotor-based bridge crack detection system

To solve the problem of crack detection for high-pier and long-span bridges, the bridge crack detection system using quadrotor was designed. The whole system includes three parts, which are unmanned aerial vehicle(UAV) system, camera system and digital image processing. By analyzing the characteristics of the bridge detection and dynamic features of quadrotor, a hardware platform was built with STM32F427 as the main control board, which met the requirements for flight power, flight control and safety. In the camera system, image quality was improved through camera correction; auxiliary information for crack automatic measurement was provided through calibration of pixel physical size and object distance measurement. In addition, a real-time image transmission scheme was designed. In digital image processing, based on noise characteristics of bridge cracks, crack binary image was acquired after median filtering, edge enhancement, threshold segmentation and morphology operations. Then, cracks could be measured automatically using improved "rectangular box method". The UAV bridge detection system presented in this paper provided a feasible scheme for solving the detection problem of cracks in long-span and high-pier bridges, and offers technical support to improve the efficiency and accuracy of bridge detection.