摘要
通过对射线底片焊缝缺陷特征分析 ,提出了用于焊缝缺陷识别的模糊神经网络模型 ,并介绍了隶属度的构造和 BP网络学习算法 .用 5 2个典型缺陷样本训练该模型后 ,对 8个缺陷样本进行识别试验 .试验结果表明 ,该方法能够提高介于模糊边界模式分类时的识别率 。
The model of fuzzy neural networks for weld defects distinguishing was described, through the analysis of the defect characters in weld of ray inspection. The construction of membership function and learning algorithm of BP networks were introduced. On the basis of the model trained by 52 type defect sample, 8 defect sample were distinguished. The experiment shows the method can improve the distinguishing rate of pattern sort in fuzzy boundary. This method excels the sort distinguishing in weld defects distinguishing.
出处
《中国矿业大学学报》
EI
CAS
CSCD
北大核心
2003年第1期92-95,共4页
Journal of China University of Mining & Technology
