Composite sleeper pore defect identification method based on Gabor multi-feature extraction and optimization

Abstract

The invention discloses a composite sleeper pore defect identification method based on Gabor multi-feature extraction and optimization. The method comprises: firstly, carrying out X-ray transillumination detection on the composite sleeper through optimized detection system parameters on the basis of the attenuation characteristic of the composite sleeper to X rays, and obtaining an original projection image; secondly, preprocessing the original ray image, including line minimum noise reduction and fuzzy enhancement; secondly, performing multi-scale and multi-direction feature extraction on theray image by utilizing a designed Gabor filter bank, and performing screening according to an energy criterion to obtain an image with prominent pore defect features; vectorizing the feature image, performing mean value removal and normalization, and completing clustering and segmentation of the pore defects by using a fuzzy C-means method; and finally, removing miscellaneous points and pseudo defects by using morphological opening and closing operation, and calculating defect geometric characteristic parameters to realize quantitative identification of the pore defects.

Description

technical field [0001] The invention relates to a composite material defect detection method, in particular to a Gabor multi-feature extraction and optimization method for composite sleeper pore defect recognition. Background technique [0002] Composite sleeper is a composite material structure made of rigid polyurethane resin foam reinforced by glass fiber yarn bundles, and is manufactured by pultrusion. Compared with other sleepers, this material has many excellent properties such as light weight, corrosion resistance, strong vibration damping, and good fatigue resistance, so it is used in rail transit engineering fields such as subways and high-speed rails. However, during the production process, there will be pore defects with excessive size inside the composite sleeper, which will seriously degrade the service performance of the composite sleeper structure, causing economic losses and safety accidents. Therefore, with the increase in the application and demand of comp...

AI Technical Summary

Problems solved by technology

However, due to the complexity of composite sleeper materials and the uncertainty of pore defects, how to accurately extract the weak pore defect characteristic information from the original X-ray image of the sleeper, and then realize the quantitative identification of defects is a key issue in the detection of composite pore defects.

Images