Intelligent tunnel crack matching detection method

Abstract

The invention discloses an intelligent tunnel crack matching detection method. The method comprises the following steps: carrying out ID numbering on each extracted crack region; then extracting a crack characteristic value in the crack area; establishing a tunnel fracture database, secondly, preprocessing the acquired tunnel crack picture; performing crack detection on the picture B to obtain coordinates of a crack area; carrying out rapid positioning and feature value extraction on the crack area through a crack matching network to obtain a feature value vector; comparing the characteristicvalue vector with the crack characteristic value corresponding to each ID number in the database, confirming the ID number of the output characteristic value, finally, extracting and storing the crackbinary image and the crack width of the C crack area in the database together with the ID number, to complete matching detection of the tunnel cracks. The method has the characteristics of high matching efficiency and good matching accuracy.

Description

technical field [0001] The invention relates to a detection method for tunnel cracks, in particular to an intelligent matching detection method for tunnel cracks. Background technique [0002] Tunnels are an important component of transportation infrastructure, but after they are put into use, a large number of cracks of different shapes will be produced due to human or natural factors. Operators need to identify and detect these cracks to determine whether the cracks will affect the tunnel hole. cause further damage inside the body and threaten driving safety. [0003] However, the current detection methods for cracks have different degrees of defects. For example, in the patent 201610551362.9 "Method for Intelligent Identification and Classification of Cracks", it is proposed to use OpenCV to read the grayscale image and convert it into a histogram, and then segment the crack through the histogram The area is merged with the crack template, and then the crack template is ...

AI Technical Summary

Problems solved by technology

However, this method requires a line array CCD camera to be equipped with a scanning motion when acquiring a two-dimensional image, and a device such as a grating is used to record the coordinates of each scanning line of the CCD camera, and to determine the corresponding position of each pixel of the image on the measured object. position, resulting in long overall image acquisition time and low measurement efficiency; and due to the increased system complexity and cost due to the existence of scanning motion and corresponding position feedback links, the image accuracy may be affected by the scanning motion accuracy. As a result, when the tunnel is uneven or has steps, it is difficult to obtain accurate position information and the measurement effect cannot be achieved

[0006] Therefore, the existing matching detection methods for tunnel cracks have the problems of low matching efficiency and poor matching accuracy.

Images