Image Crack Detection of Welding Robot under Ant Colony Algorithm
During welding,the welding robot may cause cracks due to excessive current and high welding speed,which can significantly reduce the strength of the welded joint and affect the normal operation and service life of the e-quipment.In order to accurately detect the cracks on the welding surface,this paper presented a method for detecting the surface cracks of welding robots based on ant colony algorithm.Firstly,wavelet was combined with bilateral filter to denoise the welding surface images of welding robots.According to the denoised image,the ant colony algorithm was combined with the fuzzy C-means clustering algorithm to obtain the initial number of clusters and cluster centers from the denoised image as the initial parameters of fuzzy clustering.At the same time,the welding surface was seg-mented to extract the features of cracks,thus realizing the detection of welding surface cracks of welding robots.Ex-perimental results show that the proposed method can accurately detect cracks,and it takes less than 60 seconds to detect 600 images of weld surface cracks.
Ant colonyWelding robotWeld surfaceCrackFuzzy clustering
万方数据
维普
