摘要：【中文】本发明公开了基于激光和机器视觉融合的无人机桥梁表观病害检测方法，包括如下步骤：具有激光测距装置、定位装置及图像采集装置的无人机采集目标检测面图像、目标检测面的位置及无人机与目标检测面的距离；将目标检测面图像输入病害识别神经网络识别目标检测面图像中的病害及病害在目标检测面图像中的位置；基于目标检测面图像及无人机与目标检测面的距离计算病害的尺寸参数；生成桥梁表观病害检测信息。本发明能够实现病害的自动检测，节省了大量时间成本且提高了检测的准确率，还可以自动对病害的参数进行精确计算，提高了检测效率。 【EN】The invention discloses an unmanned aerial vehicle bridge apparent disease detection method based on laser and machine vision fusion, which comprises the following steps: an unmanned aerial vehicle with a laser ranging device, a positioning device and an image acquisition device acquires an image of a target detection surface, the position of the target detection surface and the distance between the unmanned aerial vehicle and the target detection surface; inputting the target detection surface image into a disease recognition neural network to recognize the disease in the target detection surface image and the position of the disease in the target detection surface image; calculating the size parameter of the disease based on the target detection surface image and the distance between the unmanned aerial vehicle and the target detection surface; and generating apparent bridge disease detection information. The invention can realize automatic detection of diseases, save a large amount of time and cost, improve the detection accuracy, automatically and accurately calculate the parameters of the diseases and improve the detection efficiency.