基于多传感器信息融合的铜带表面缺陷检测研究  

Research of Surface Defects Detection on Copper Strips Based on Mulit-sensor Data Fusion

作　　者：黄云龙[1] 

机构地区：[1]衢州职业技术学院,浙江衢州324000

出　　处：《煤炭技术》2011年第2期143-145,共3页Coal Technology

摘　　要：结合铜带表面缺陷检测这一应用背景,提出通过多传感器信息融合的方法提高检测系统整体性能。缺陷检测系统使用红外、可见光和激光3种图像传感器结合,采用模糊逻辑和神经网络进行传感器管理,小波变换进行图像融合.实验结果表明该方法提高了缺陷检测和分类能力。With the application background of surface defects detection for copper strips, the authors proposed a method to enhance the stability of the overall system using multi-sensors information fusion algorithm. The system uses infrared light detection, visible light detection and laser detection to deal with surface defects. Furthermore, it combines fuzzy logic algorithm with neural network to carry out sensor management and uses wavelet transformation to fuse images. The experimental results demonstrate that the proposed method improves the recognization and classification rate for defects detection.

关 键 词：信息融合 无损检测 传感器管理 神经网络 模糊逻辑 小波变换 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]