Application of Machine Vision in Structural Deformation and Health Monitoring

There are two main methods of structural health monitoring. Among them, the traditional structure health monitoring technology is mainly artificial, which has some problems such as inflexibility, large error, high cost and difficult to adapt to the change of natural environment. The structural health monitoring method based on machine vision has the characteristics of flexible measuring point, high accuracy, fast speed and no contact. A variety of machine vision technologies, such as image acquisition, image processing, three-dimensional vision and deep learning technologies, have made great progress, and their application scenarios are constantly expanding. This paper is based on infrared image acquisition technology, 3D vision acquisition technology, image stitching technology, stereo vision technology four perspectives. The improvement of machine vision technology in the field of structural health monitoring is described in detail. The development trend of machine vision acquisition technology and image processing technology and the huge growth space of machine vision technology are analyzed. The application range of these key technologies is also introduced. The application results in building crack detection, seepage detection and fire detection are summarized, and the future development of this technology is prospected from the aspects of algorithm robustness.