针对现有混凝土构件裂缝人工检测操作不仅费时、费力,而且易出现错检、误检、漏检,以及部分位置难以开展检测的问题,提出一种基于深度学习YOLOX(You Only Look Once)算法的混凝土构件裂缝智能化检测方法;首先采集、整理包含各类混凝土构件的典型裂缝图像,并通过图像数据增强建立Pascal VOC数据集,然后基于Facebook公司开发的深度学习框架Pytorch,利用数据集训练YOLOX算法,并进行裂缝识别和验证;将训练完成后YOLOX算法移植至搭载安卓系统的手机端,进行现场实时检测操作.结果表明:在迭代次数为700 时,混凝土构件裂缝识别精度可达88.84%,能有效筛分混凝土构件表面裂缝,并排除其他干扰项,证明了所提出的方法对裂缝具有较高的识别精度和广泛的适用性;经试验测试,移植至手机端的YOLOX算法能在提升便携性的同时保证高效、准确的检测效果,具有良好的应用前景.
Intelligent Detection Method for Cracks of Concrete Members Based on Deep Learning YOLOX Algorithm
In view of the problem that the existing artificial detection technology for cracks of concrete members was not only time-consuming and laborious but also prone to misdiagnosis,false detection,miss detection,and difficulties in detecting some locations,an intelligent detection method for cracks of concrete elements based on deep learning YOLOX(You Only Look Once)algorithm was proposed.Typical crack images of various concrete members were firstly collected and sorted out,and a Pascal VOC dataset was established through image data enhancement.On the basis of deep learning framework Pytorch developed by Facebook,YOLOX algorithm was then trained and verified for crack identification by using the dataset.YOLOX algorithm after training was transplanted to the mobile phone terminal with Android system for on-site real-time detection.The results show that the crack identification accuracy concrete members can reach 88.84%when the iteration number is 700.Cracks on the surface of concrete members can be effectively screened out and other interference items can be excluded,which indicates that the proposed method has high identification accuracy and wide applicability for cracks.Through the test,YOLOX algorithm transplanted to mobile phone terminals can not only improve portability but also ensure the efficient and accurate detection effect,which has a good application prospect.
deep learningYOLOX(You Only Look Once)algorithmconcrete membercrack identification
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