Experimental Design of Rail Surface Defect Classification Based on Machine Vision
With the rapid development of urban rail transit,the realization of real-time detection of rail surface defects is of great significance to the steady development of the railway industry.Detection of rail surface defects in real time is a key issue,and needs to be solved to ensure the safety of railway operations.In view of this,firstly,a simulation experimental method for rail surface defect detection based on machine vision is designed,and an image acquisition module,image preprocessing module and defect classification module are built.Secondly,a self-fitting brightness adjustment algorithm is proposed to complete the pixel value statistics,and finally obtain the image with clear defect features.The testing result shows that the method can quickly identify and classify the surface defect information of the classified rail.
detection of rail surface defectsmachine visionimage processingdefect classification
万方数据
维普
