Method for detecting girder cracks based on image processing

Abstract

The invention relates to a method for detecting girder cracks based on image processing, and belongs to the field of malfunction diagnosis technology and signal processing analysis technology. The method comprises the following steps: firstly establishing a feature training sample set of girder cracks, and manufacturing a Ground Truth set of sample images, establishing a girder crack detection classifier based on a structural random forest; then performing stitching on crack images within each time period among acquired images; using the generated girder crack detection classifier to perform rough edge detection for girder cracks on the stitched crack images to obtain a rough edge detection result; finally conducting accurate crack selection and location on the rough edge detection result. According to the invention, a well trained girder crack detection classifier can extract crack information in square girders in an efficient, rapid and accurate manner, eliminates malfunction in an in-time and rapid manner, and increases economic benefits and guarantees personal safety of working staff.

Description

technical field [0001] The invention relates to a steel beam crack detection method based on image processing, which belongs to the field of fault diagnosis technology and signal processing and analysis technology. Background technique [0002] Once cracks appear on the surface of the steel beams used by industries and enterprises, it will cause great economic losses and serious personal safety problems, especially the top guide rails in the production line. The lower extrusion component and stress accumulation will lead to frequent failure and fracture. At present, workshop staff can only rely on visual inspection to find cracks, which is heavy workload, low efficiency, and time-consuming. Therefore, an effective automatic detection method is urgently needed. [0003] At present, the non-destructive testing techniques commonly used in steel structures include macroscopic inspection, ultrasonic, magnetic particle, penetration, stress-strain testing, etc., but it is difficu...

AI Technical Summary

Problems solved by technology

[0006] Based on the above problems, the present invention provides a steel beam crack detection method based on image processing. When the guide rail on the top of the production line is subjected to upward or downward extrusion force and stress accumulation during the operation of the hanger roller, damage and fracture occur frequently At present, it solves the problem that the workshop staff can only rely on visual inspection to find cracks, the detection workload is heavy, the efficiency is low, and the time is long. Other non-destructive testing techniques are also difficult to effectively detect steel beams.

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