基于细胞神经网络的桥梁裂痕诊断研究  

Study of bridge crack diagnosis based on cellular neural network

作　　者：张福新[1] 李国东[1] 

机构地区：[1]新疆财经大学应用数学学院,新疆乌鲁木齐830000

出　　处：《大众科技》2014年第1期26-29,共4页Popular Science & Technology

基　　金：国家教育部人文社会科学基金(批准号:13YJAZH040);新疆维吾尔自治区高校科研计划项目(项目编号:XJEDU2013I26)

摘　　要：为了更好的监测桥梁裂痕,文章提出了一种改进的细胞神经网络桥梁裂痕图像识别方法。该方法通过一定的图像处理,建立裂痕网络和细节网络,同时增加了裂痕相似网络模型,避免了仅对裂痕特征提取信息不能准确识别裂痕的问题。实验证明,改进的裂痕识别算法实现简单,识别桥梁裂痕准确率高,达到了实时识别技术的要求。In order to detecting the bridge crack, we come up with a fixed way of bridge rift image detection by using cellular neural networks. By image processing, building rift networks and details networks and adding the model of similarity rift networks. It can avoid the problem that can not accurately detect crack by only taking the crack feature value. The experiment proved that fixed crack detect computing is easy to do, more accurate to detect the cracks on the road and can reach the standard level of current detect technique.

关 键 词：裂痕诊断 桥梁裂痕 细胞神经网络 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]