Welding quality evaluation method and system based on ultrasonic image feature fusion

Abstract

The invention provides a welding quality evaluation method and system based on ultrasonic image feature fusion, and relates to the technical field of welding quality detection. The method and system aim at obtaining three-dimensional information of internal defects of a welding joint through B scanning and C scanning images of ultrasonic detection, fusing a plurality of defect feature quantities through information entropy, realizing comprehensive characterization of welding quality and improving welding quality, and evaluation information is comprehensive and high in accuracy. The method comprises the steps that S1, ultrasonic detection is conducted on a backfill type friction stir spot welding joint, and a B scanning image and a C scanning image of a welding area are collected; S2, the obtained B scanning image and the C scanning image are analyzed and processed, effective information in the images and defect features in the welding spots are extracted, and three-dimensional information representation of the welding quality is formed; and S3, different weight coefficients are endowed to the characteristic quantity in the three-dimensional information representation by using the information entropy, and the weight coefficients are fused into a comprehensive index as an evaluation result. The technical scheme provided by the invention is suitable for the welding quality evaluation process.

Description

technical field [0001] The invention relates to the technical field of welding quality detection, in particular to a welding quality evaluation method and system based on ultrasonic image feature fusion. Background technique [0002] Backfill friction stir spot welding is a new type of welding technology. Because there is no keyhole after welding, the joint has high strength and good quality, it is widely used in the welding of commonly used light metals such as aluminum alloy and magnesium alloy in aerospace, automobile, shipbuilding and other fields. However, in the welding process, improper selection of welding parameters will lead to insufficient backfilling, hook defects, holes and other defects inside the joint. These defects are often easy to expand into cracks, thereby reducing the mechanical properties of the product. Therefore, the detection of welding defects and the evaluation of welding quality are very important. [0003] Traditional welding quality detection...

AI Technical Summary

Problems solved by technology

This patent is mainly for the analysis of A-scan waveforms. The larger the scanning range, the more A-scan waveforms will be obtained, which will lead to problems such as large amount of analyzed data and low analysis efficiency.

More importantly, the A-scan waveform is a one-dimensional signal, and it is difficult to fully characterize the distribution characteristics of welding defects in three-dimensional space, so the ability of this technology to evaluate welding quality is limited

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