Application of a new feature extraction and optimization method to surface defect recognition of cold rolled strips  

作　　者：Guifang Wu Ke Xu Jinwu Xu 

机构地区：[1]National Engineering Research Center for Advanced Rolling Technology, University of Science and Technology Beijing, Beijing 100083, China [2]Electronic Information Engineering College, Henan University of Science and Technology, Luoyang 471003, China

出　　处：《Journal of University of Science and Technology Beijing》2007年第5期437-442,共6页北京科技大学学报（英文版）

基　　金：This work was financially supported by the National High Technology Research and Development Program of China (No.2003AA331080 and 2001AA339030);the Talent Science Research Foundation of Henan University of Science & Technology (No.09001121).

摘　　要：Considering that the surface defects of cold rolled strips are hard to be recognized by human eyes under high-speed circumstances, an automatic recognition technique was discussed. Spectrum images of defects can be got by fast Fourier transform （FFF） and sum of valid pixels （SVP）, and its optimized center region, which concentrates nearly all energies, are extracted as an original feature set. Using genetic algorithm to optimize the feature set, an optimized feature set with 51 features can be achieved. Using the optimized feature set as an input vector of neural networks, the recognition effects of LVQ neural networks have been studied. Experiment results show that the new method can get a higher classification rate and can settle the automatic recognition problem of surface defects on cold rolled strips ideally.Considering that the surface defects of cold rolled strips are hard to be recognized by human eyes under high-speed circumstances, an automatic recognition technique was discussed. Spectrum images of defects can be got by fast Fourier transform （FFF） and sum of valid pixels （SVP）, and its optimized center region, which concentrates nearly all energies, are extracted as an original feature set. Using genetic algorithm to optimize the feature set, an optimized feature set with 51 features can be achieved. Using the optimized feature set as an input vector of neural networks, the recognition effects of LVQ neural networks have been studied. Experiment results show that the new method can get a higher classification rate and can settle the automatic recognition problem of surface defects on cold rolled strips ideally.

关 键 词：cold rolled strip surface defect neural networks fast Fourier transform （FFT） feature extraction and optimization genetic algorithm feature set 

分 类 号：TG38[金属学及工艺—金属压力加工]