机械科学与技术2017，Vol.36Issue(11)：1785-1790,6.DOI:10.13433/j.cnki.1003-8728.2017.1124
改进组合分类器的冷轧带钢表面缺陷识别研究
Study on Surface Defect Recognition of Cold Rolled Steel Strip by Improving Combinationclassifier
摘要
Abstract
For the cold-rolled strip that has various types of surface defects and complex form,there will be insensitive individual defects and low recognition rate if a single classification is used to identify classification.Therefore it probably results in data classification processing feature size is too large,the robustness and stability of the system is difficult to ensure.The method based on the the improved combination classifier is put forward.It will optimize BP neural network and probabilistic neural network,combining the improved support vector machine.Moreover,it will use complementary classification information to classify.Optimum classification system can be constituted.The experimental results show that the combination of the improved classifier makes up for the lack of a single classifier Network training.For each type of defect recognition,the accuracy is high.It can increase the overall classification generalization ability.The recognition accuracy rate is more than 95％.In short,there is efficient recognition and practical value.关键词
表面缺陷/冷轧带钢/组合分类器/分类Key words
surface defect/cold roiled steel strip/combination classifiers/classification分类
信息技术与安全科学引用本文复制引用
化春键,周海英..改进组合分类器的冷轧带钢表面缺陷识别研究[J].机械科学与技术,2017,36(11):1785-1790,6.基金项目
国家自然科学基金项目(61104213)与中央高校基本科研业务费专项资金项目(JUSRP11008)资助 （61104213）
