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土木工程中的无损检测技术应用
              土木工程中的无损检测技术应用

              DOI:10.11973/wsjc240239



              基于 YOLOv4 算法的建筑大面积现浇混凝土地坪

                                            施工细小裂缝检测




                                                           卢亚荣
                                         (陕西省建筑科学研究院有限公司,西安 710082)

                       摘  要:受混凝土材料收缩以及温度等作用效应,建筑施工中混凝土地坪结构开裂问题较为普
                   遍,会直接影响到地坪底部地基的稳定性。传统方法对裂缝结构特征的提取方式较为单一,在对地
                   坪施工细小裂缝检测中存在误差,为此,基于YOLOv4算法研究建筑大面积现浇混凝土地坪施工细
                   小裂缝检测方法。首先在温度场下定量分析地坪施工形变分量;其次确定大面积地坪形变分量中
                   的裂缝信息;再采用均值偏移滤波聚类细小裂缝特征;最后基于YOLOv4算法融合细小特征检测混
                   凝土地坪细小裂缝。试验结果表明,所研究方法可以较为完整地提取混凝土地坪细小裂缝特征,在
                   不同类型裂缝目标检测中精度可达98%,具有应用价值。
                       关键词:YOLOv4算法;混凝土地坪;细小裂缝
                       中图分类号:TU755.7;TG115.28      文献标志码:A    文章编号:1000-6656(2025)04-0039-05

                            Detection of small cracks in large area cast in place concrete flooring

                                         construction based on YOLOv4 algorithm


                                                          LU Yarong
                               (Shaanxi Construction Science Research Institute Co., Ltd., Xi'an 710082, China)
                      Abstract: Due to the shrinkage of concrete materials and temperature effects, cracking of concrete floor structures
                   is common in construction, which directly affects the stability of the foundation at the bottom of the floor. The traditional
                   method for extracting crack structure features is relatively single, and there are errors in detecting small cracks in floor
                   construction. Therefore, based on YOLOv4, a method for detecting small cracks in large-area cast-in-place concrete
                   floor construction was studied. The deformation component of floor construction under temperature field was quantified,
                   the crack information in the deformation component of large-area flooring was determined. Mean shift filtering was used
                   to cluster small crack features, small cracks in concrete floors were detected based on YOLOv4 fusion of small features.
                   The results showed that the proposed method could extract the characteristics of small cracks in concrete floors more
                   comprehensively, with an accuracy of up to 98% in target detection of different types of cracks, and had practical value.
                      Key words: YOLOv4 algorithm; concrete flooring; small crack

                  城市中大型商业综合体、地下停车场以及工业                          出现开裂问题。大部分地坪在使用过程中都会存在
              厂房等建筑的基础设备常采用混凝土地坪,但该材                            裂缝,其不仅会影响美观,还会影响整体耐久性,尤
              料的抗拉强度较低,在建筑大面积地坪施工过程中,                           其是细小裂缝不易被第一时间察觉,故需要对混凝
              由于混凝土的特性以及地坪的受载情况,地坪经常                            土的材料随机分布情况进行跟踪,结合不同结构力
                                                                学性质以及物理参数对地坪结构的影响,推演出混
                 收稿日期:2024-05-24                                凝土地坪施工中细小裂缝的演化过程,以此完成细
                 作者简介:卢亚荣(1974—),女,本科,高级工程师,主要从事建
                                                                小裂缝的预测和检测。
              筑工程质量检测方面的研究工作
                 通信作者:卢亚荣,y562656@163. com                           随着视觉识别技术与计算机技术的快速发展,

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                                                                                         2025 年 第 47 卷 第 4 期
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