Method and system for detecting pavement crack diseases

Abstract

The invention provides a method for detecting pavement crack diseases. The method includes steps of emitting laser light beams towards lanes by a laser generator and forming series bent marked lines on to-be-detected pavements; acquiring the series bent marked lines by a laser marked line image acquisition device under the control of image acquisition control signals on the basis of preset acquisition cycles to obtain light spot images and carrying out low-pass filter processing on the light spot images by an information processing system to obtain low-pass filtered continuous cross-section numerical images; carrying out full-spectrum fidelity processing on the light spot images obtained by the information processing system to obtain full-spectrum cross-section numerical images; carrying out difference on the full-spectrum cross-section numerical images obtained by means of full-spectrum fidelity processing and the low-pass filtered continuous cross-section numerical images obtained by means of low-pass filter processing to obtain pulse elevation numerical images of the pavement crack diseases. Filter parameters for low-pass filter are related to light spots formed by the series bent marked lines. Filter parameters for the full-spectrum fidelity processing are related to the light spots formed by the series bent marked lines. The method has the advantage that the work efficiency can be improved.

Description

technical field [0001] The invention relates to the field of road surface detection, in particular to a method and system for measuring cracks and potholes on pavements of roads or other similar structures. Background technique [0002] At present, in the field of pavement crack detection, the two-dimensional damage of cracks mainly adopts the method of manual direct observation and interpretation and the crack identification method of crack two-dimensional image. The main problem of using manual direct observation and interpretation is that real-time detection cannot be carried out and normal driving safety is affected, and the detection efficiency and detection accuracy need to be improved. [0003] The crack identification method based on the crack two-dimensional image is based on the difference between the illumination characteristics of cracks under certain lighting conditions and the road surface itself, but this is not the essential characteristic of cracks, because ...

AI Technical Summary

Problems solved by technology

The main problem of using manual direct observation and interpretation comparison is that it cannot perform real-time detection and affects normal driving safety, and the detection efficiency and detection accuracy need to be improved.

[0003] The crack identification method based on the crack two-dimensional image is based on the difference between the illumination characteristics of cracks under certain lighting conditions and the road surface itself, but this is not the essential characteristic of cracks, because the principle of two-dimensional image sensing cannot be completely overcome , the interference factors such as lighting conditions, shadows, road oil, sundries and other interference factors in the acquisition process, the information obtained only through the two-dimensional image of the crack cannot extract the complete crack, and cannot reflect the depth characteristics of the crack

[0004] Recently, a three-dimensional visualization measurement system using GNSS (Global Navigation Satellite System) has also been produced. This system collects data through connecting satellite systems and transmits it to dedicated equipment for reading and writing. It can achieve more accurate measurement results, but its price Expensive, not suitable for general high volume use

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