基于核Fisher判别分析的点焊质量评估

通过对点焊过程电极位移信号的实时采集和特征分析,利用模糊化方法将电极位移信号映射为15×25模式矩阵.依据不同焊接电流参数下位移信号的模式特征将位移信号的模式分为5类,分别对应不同的焊点质量.以不同类别焊点的模式矩阵构建输人数据空间,利用核Fisher判别技术将低维数据空间的非线性分类问题转化为高维特征空间的线性分类问...

Quality estimation of resistance spot welding based on kernel fisher discriminant analysis

In this research,the displacement signal of the resistance spot welding process is monitored and mapped into a 15×25 element bipolarized matrix by fuzzy theory method.Some welded spots with different welding currents,are classified into five classes according to the prototype pattern matrices.These pattern matrices,which represent different weld quality respectively,are used to construct the input data space.By using Kernel Fisher Discriminant Analysis(KFDA) technology,a nonlinear classification problem of the original data space can be converted to a linear one in feature space of high dimension.An effective pattern recognition system is developed,which realizes quality estimation of the welded spots.The results of cross-validation test show that the method utilizing pattern matrix of the electrode displacement signal to characterize formation process of nugget is effective.At the same time,the Fisher algorithm introduced kernel technology improves the recognition accuracy of the welded spot pattern under the small sample circumstance.