信息化大数据模型的道路裂痕识别和分析

Road Crack Identification and Analysis Based on Information Big Data Model

针对市政工程出现的路面裂缝带来的安全隐患问题,采用基于智能摄像机的图像采集技术实现市政道路异常数据信息的获取。通过改进型CLAHE算法对采集到的图像数据信息进行处理,对获取的裂缝图像进行灰度计算,提高了图像识别能力。通过构建新型DE-BP神经网络算法模型,实现道路数据信息的异常故障诊断与分析,大大提高了市政道路裂痕判断能力。实验表明,本研究的方法大大提高了裂缝图像识别的准确率,增加了市政建设的管理能力。

Aiming at the potential safety hazards caused by road cracks in municipal engineering,a new type of fault diagnosis method for municipal road cracks is proposed.This method constructs a new type of fault diagnosis scheme,realizes the processing of image data information.Through the improved CLAHE algorithm,it preprocesses the crack image to form a gray image,and improve the image recognition ability.It builds a new DE-BP algorithm torealize the abnormal fault diagnosis of road data information.Experiments show that the method can not only improve the accuracy of crack image recognition,but also increase the training speed and reduce the time required for training.