基于LCSPSO-BTSVM的焊缝表面缺陷检测

Weld Surface Defect Detection Based on LCSPSO-BTSVM

针对焊缝表面缺陷PSO优化BTSVM的两个参数容易陷入局部最优、伪随机多样性低和计算精度低的问题,提出一种LCSPSO优化BTSVM参数的方法。首先,改进PSO算法,引入莱维飞行策略、Circle混沌映射与单纯形反射操作确保两个参数取得全局最优解,提高分类准确率;其次,提取预处理焊缝表面缺陷图像的特征;最后,设计合理的分类器利用改进的方法对焊缝表面缺陷进行分类检测并与其他算法作对比。试验结果表明,LCSPSO优于其他算法,分类精度比改进前提高了12.03%,平均分类准确率99.07%。

Aiming at the problems that the two parameters of BTSVM optimized by weld surface defect PSO are easy to fall into local optimum,low pseudo-random diversity and low calculation accuracy,a method of LCSPSO to optimize BTSVM parameters is proposed.Firstly,improve the PSO algorithm,introduce Levi's flight strategy,Circle chaotic map and simplex reflection operation to ensure the global optimal solution of the two parameters and improve the classification accuracy.Reasonable classifier uses the improved method to classify and detect weld surface defects and compares it with other algorithms.The test results show that LCSPSO is superior to other algorithms,the classification accuracy is 11.2%higher than that before improvement,and the average classification accuracy is 99.19%.