摘要
针对冻融裂缝特征收敛效果差,路面冻融裂缝检测精准度低的问题,设计了基于特征图的路面冻融裂缝红外检测算法。基于红外热成像原理,联合异性温度场重构和双边滤波理论方法,形成新的路面冻融裂缝红外热图像温度场重构方法,构建冻融裂缝特征矩阵,将路面冻融裂缝红外图像作为输入,优化卷积神经网络的卷积核权值,构建基于特征图的检测方法,获取最佳路面冻融裂缝红外成像检测结果。结果表明:该算法温度场重构后可使路面冻融裂缝红外图像更加清晰,并保留图像的边缘信息和轮廓,且在不同类型噪声干扰下,温度场重构后图像始终具有较高的峰值信噪比。该方法可检测到了不同类型的路面冻融裂缝,可以提升道路安全运维效果。
Aiming at the problem of poor convergence effect of freeze-thaw crack characteristics and low accuracy of pavement freeze-thaw crack detection,an infrared detection algorithm for pavement freeze-thaw cracks based on feature maps was designed.Based on the principle of infrared thermal imaging,a new method for reconstructing the temperature field of pavement freeze-thaw crack infrared thermal images is formed by combining anisotropic temperature field reconstruction and bilateral filtering theory.A freeze-thaw crack feature matrix is constructed,and the pavement freeze-thaw crack infrared image is used as input to optimize the convolution kernel weights of the convolutional neural network.A feature map based detection method is constructed to obtain the best pavement freeze-thaw crack infrared imaging detection results.The results show that the algorithm can make the infrared images of road freeze-thaw cracks clearer after temperature field reconstruction,and preserve the edge information and contour of the image.Moreover,under different types of noise interference,the reconstructed temperature field image always has a high peak signal-to-noise ratio.This method has detected different types of pavement freeze-thaw cracks,which can improve the effectiveness of road safety operation and maintenance.
作者
张建勋
ZHANG Jianxun(Pingdingshan Longze Highway Engineering Co.,Ltd.,Pingdingshan 467000,China)
出处
《粉煤灰综合利用》
2025年第2期164-168,共5页
Fly Ash Comprehensive Utilization
关键词
路面冻融裂缝
卷积神经网络
红外成像
热图像消噪
裂缝检测
机器学习
road freeze-thaw cracks
convolutional neural network
infrared imaging
thermal image denoising
crack detection
machine learning
