摘要
研究了基于粗糙集理论的在线铝合金点焊质量判定的新方法,选取焊接过程中电极位移、电极压力两个参数的八个特征量构成知识表示系统,采用自组织特征映射网络(SOM网络)离散连续属性值、基于差别矩阵的属性约简算法对获取的信息进行处理,提取判别规则,进而通过判别规则来完成焊点质量的分类.该方法不仅降低特征空间的维数、减少质量分类的工作量、降低了信息存储量,而且点焊质量判断准确率可以达到97.06%.
The new method of quality judgment about on-line aluminum alloy spot welding was studied,which was based on the rough set theory. The eight characters selected from two parameters (electrode displacement and electrode force in the weld process) constituted the knowledge representation system. The new method dealt with the obtained information by adopting the discretized continuous attribute algorithm with the self-organizing feature map network(SOM) and the attribute reduction algorithm based on discernibility matrix,picked up the distinguish rule,then completed the classification of spot welding quality by the rule. The method can not only reduce the dimensions of the feature space,the workload of quality classification and the information memory capacity,but also can make the accuracy of the spot weld quality judgment reach 97.03%.
出处
《焊接学报》
EI
CAS
CSCD
北大核心
2009年第7期21-24,共4页
Transactions of The China Welding Institution
基金
天津市自然科学基金资助项目(05YFJMJC02600)
天津科技大学人才引进资助项目(20050404)
关键词
质量判定
粗糙集
属性离散
属性约简
电阻点焊
quality judgment
rough set
attribute discrimination
attribute reduction
resistance spot welding
