Application of Artificial Neural Networks to Strip Steel Surface Defect Diagnosis

摘要：

Based on the analysis of strip steel surface quality examination carried at home and abroad, the paper analyzes flaws and corresponding factors beginning with the design of examination system. It studies deeply the related theories and key techniques of strip steel surface quality examination system, applied neural networks for strip steel surface defect recognizing successfully. It is applied successfully to whole flow quality control technique and equipment composite diagnosis system (TQC-DS) in a steel company.

关键词： Strip steel surface defect diagnosis Neural network Whole flow quality control Defect recognition

作者: Hu Qinghe Xu Jiazhuo Chen Weidong Yang Dalei

作者单位: College of Information & Science Engineering, Northeastern University, Shenyang 100004, China BaoSteel Industry Inspection Corp. Shanghai 201900,China

会议类型: 国际会议

会议名称: 2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)

会议地点: 广西桂林

会议语种:英文

页码: 2476-2479

在线出版日期: 2009-06-17（万方平台首次上网日期，不代表论文的发表时间）