Steel Cord Conveyor Belt Defect Recognition Based on PSO-SVM Considering Shrinkage Factor

For the steel cord conveyor belt many types of defect signal classification is studied and the classification method based on the support vector machine optimized by particle swarm algorithm considering shrinkage factor(PSO-SF-SVM) is proposed. The PSO-SF-SVM method was carried out to achieve the defect classification for steel cord conveyor belt. The result shows the PSO-SF-SVM method has high classification accuracy rate and short training and testing time. The work provides a kind of effective defect classification method for steel cord conveyor belt in coal mine.