Research on Online Recognition Algorithm of Rail Profile Type Based on GA-SVM
Aiming at the low recognition rate of rail profile automatic detection in daily rail transit operation and mainte-nance,a high-precision rail profile online recognition algorithm based on geometric descriptors and support vector machine(SVM)was proposed.Structure light sensor was used to collect rail profile data,and geometric denoising algorithm was used to re-move outliers and resampling the profile.The feature extraction of different types of rail profiles was carried out through the profile geometric descriptors,and the profile feature dataset was made for SVM training.Genetic algorithm(GA)was used to optimize the parameters of SVM model.The optimized SVM model was used for rail profile detection and compared with the traditional profile recognition method.The results show that the proposed GA-SVM model using geometric descriptors can achieve an average accu-racy rate of 99.62%and a single-frame contour recognition time of 6.43 ms.It can effectively improve the accuracy and high speed of profile recognition,meet the needs of online detection of rail vehicles,and provide theoretical and technical support for automated track detection.
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