Automation in Construction最新文献_第7页

Multi-equipment collaborative optimization scheduling for intelligent construction scene 智能施工场景的多设备协同优化调度

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2024-09-23 DOI: 10.1016/j.autcon.2024.105780

Zhansheng Liu , Guoliang Shi , Dechun Lu , Xiuli Du , Qingwen Zhang

{"title":"Multi-equipment collaborative optimization scheduling for intelligent construction scene","authors":"Zhansheng Liu , Guoliang Shi , Dechun Lu , Xiuli Du , Qingwen Zhang","doi":"10.1016/j.autcon.2024.105780","DOIUrl":"10.1016/j.autcon.2024.105780","url":null,"abstract":"<div><div>How to realize the efficient scheduling of construction equipment and ensure the construction quality is the key problem that restricts the development of intelligent construction technology. This paper proposes a multi-equipment collaborative optimization scheduling method for intelligent construction scene. Firstly, a logical model of intelligent construction scene is proposed, and the characteristics and requirements of construction in intelligent construction scene are clarified. Considering the relationship between construction processes and the control requirements of construction quality, an intelligent planning model of multi-equipment collaborative scheduling scheme is established. Aiming at the problem of equipment scheduling analysis, an improved non-dominant classification genetic algorithm (NSGA-II) is proposed. According to the solution results of the improved NSGA-II, the data mapping relationship between the scheduling scheme and the construction completion time and construction energy consumption is established. The verification and application of the proposed method are carried out by a cable truss structure experimental model.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":null,"pages":null},"PeriodicalIF":9.6,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0926580524005168/pdfft?md5=4e1d66a090d4b679e31382385c84fe57&pid=1-s2.0-S0926580524005168-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142312452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Vision-guided robot for automated pixel-level pavement crack sealing 用于自动像素级路面裂缝密封的视觉引导机器人

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2024-09-23 DOI: 10.1016/j.autcon.2024.105783

Jianqi Zhang , Xu Yang , Wei Wang , Hainian Wang , Ling Ding , Sherif El-Badawy , Zhanping You

引用次数: 0

Data integration using deep learning and real-time locating system (RTLS) for automated construction progress monitoring and reporting 利用深度学习和实时定位系统（RTLS）进行数据整合，实现自动化施工进度监测和报告

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2024-09-23 DOI: 10.1016/j.autcon.2024.105778

Dena Shamsollahi , Osama Moselhi , Khashayar Khorasani

{"title":"Data integration using deep learning and real-time locating system (RTLS) for automated construction progress monitoring and reporting","authors":"Dena Shamsollahi , Osama Moselhi , Khashayar Khorasani","doi":"10.1016/j.autcon.2024.105778","DOIUrl":"10.1016/j.autcon.2024.105778","url":null,"abstract":"<div><div>The shift towards automated progress monitoring using new technologies for efficient delivery of construction projects has received significant attention. The application of vision-based techniques for object recognition and real-time locating system (RTLS) for object localization has been widely studied. However, a single technology cannot provide complete information needed to determine the status of tracked elements on a job site. This paper presents an integrated method for progress monitoring through recognition and localization of elements in construction sites. This method integrates data derived from a deep learning model and Ultra-wideband (UWB) system, and reports each element's ID, location, visual data and capture time. Such information is essential for project managers to assess progress on site. The method is validated in a mechanical room, a challenging environment for RTLS and object recognition models due to signal interferences and occlusions. The findings suggest further research on improving integrated methods for efficient progress reporting.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":null,"pages":null},"PeriodicalIF":9.6,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0926580524005144/pdfft?md5=a2adecd5ce30de2f9f8d66dd155b3629&pid=1-s2.0-S0926580524005144-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142312455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing intelligent compaction quality assessment utilizing mathematical-geographical data processing 利用数学地理数据处理加强智能压实质量评估

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2024-09-23 DOI: 10.1016/j.autcon.2024.105786

Chi Cheng , Xuefei Wang , Jiale Li , Jianmin Zhang , Guowei Ma

{"title":"Enhancing intelligent compaction quality assessment utilizing mathematical-geographical data processing","authors":"Chi Cheng , Xuefei Wang , Jiale Li , Jianmin Zhang , Guowei Ma","doi":"10.1016/j.autcon.2024.105786","DOIUrl":"10.1016/j.autcon.2024.105786","url":null,"abstract":"<div><div>The advent of Intelligent Compaction (IC) has revolutionized real-time monitoring of compaction quality. The Compaction Meter Value (CMV) is widely used in highway construction but demonstrates insufficient reliability, which generates challenges for accurate quality assessment. A mathematical-geographical-based processing method is proposed to refine IC datasets. Six datasets from highway compaction sites were used to verify the effectiveness of the method. Statistical analysis is employed to cleanse redundant values, while a near-neighbor weighted method, accounting for spatial distribution characteristics, is utilized to identify and replace outliers. CMV has instability under complex influence factors, and it shows the best applicability in the subgrade. The optimized datasets perform well in correlation models, showcasing a significant improvement in quality evaluation effectiveness. This paper aims to optimize the utilization of IC datasets, thereby bolstering the reliability of CMV. The proposed method advocates integration into the IC system to promote highway construction quality.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":null,"pages":null},"PeriodicalIF":9.6,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142312453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bayesian continuous wavelet transform for time-varying damping identification of cables using full-field measurement 利用全场测量贝叶斯连续小波变换识别电缆的时变阻尼

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2024-09-21 DOI: 10.1016/j.autcon.2024.105791

Junying Wang , Qiankun Zhu , Qiong Zhang , Xianyu Wang , Yongfeng Du

{"title":"Bayesian continuous wavelet transform for time-varying damping identification of cables using full-field measurement","authors":"Junying Wang , Qiankun Zhu , Qiong Zhang , Xianyu Wang , Yongfeng Du","doi":"10.1016/j.autcon.2024.105791","DOIUrl":"10.1016/j.autcon.2024.105791","url":null,"abstract":"<div><div>Cables serve as the primary load-bearing element in cable-stayed bridges, making their damping level critical for structural safety evaluation. Traditional operational modal analysis (OMA) faces challenges in damping identification due to result discreteness, and limited sensor deployment often leads to the loss of crucial modal information. This paper proposes a Bayesian continuous wavelet transform with Gabor wavelet (BCWT-G) method for time-varying damping identification using full-field measurement data. A computer vision technique combining the pyramid grafting network (PGNet) with neighboring frame pixel fitting (NFPF) is used to accurately capture full-field vibration data. The time-frequency domain properties of these data are then extracted and incorporated into a Bayesian probabilistic estimation framework for modal updating. The proposed method was validated through numerical simulations using a physics-based graphics model (PBGM), and actual cable testing under complex environments, demonstrating its effectiveness and robustness in identifying the time-varying dynamic characteristics of cables.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":null,"pages":null},"PeriodicalIF":9.6,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142312450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Intelligent design of key joints in aerial building machine using topology optimization and generative adversarial network 利用拓扑优化和生成式对抗网络智能设计空中造物机的关键关节

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2024-09-21 DOI: 10.1016/j.autcon.2024.105747

Zhuang Xia , Jiaqi Wang , Yongsheng Li , Limao Zhang , Changyong Liu

{"title":"Intelligent design of key joints in aerial building machine using topology optimization and generative adversarial network","authors":"Zhuang Xia , Jiaqi Wang , Yongsheng Li , Limao Zhang , Changyong Liu","doi":"10.1016/j.autcon.2024.105747","DOIUrl":"10.1016/j.autcon.2024.105747","url":null,"abstract":"<div><div>Joints are crucial connections in an aerial building machine (ABM), yet they often undergo experience-based local optimization design. This paper presents an intelligent design method for key joints in the ABM using a generative adversarial network (GAN), aiming to achieve new and superior global optimization schemes. A database of topology-optimized structures is fed into the boundary equilibrium GAN (BEGAN) for training, which in turn generates innovative and diverse design schemes. The optimal scheme selection under multi-working conditions is then realized by the multiple-attribute decision-making (MADM) method. A case study of an ABM joist confirms the effectiveness of this method, showing it meets safety requirements under various conditions and achieves significant improvements (43.45 % for construction, 43.67 % for jacking, and 42.89 % for shutdown). Additionally, the BEGAN model surpasses existing generative models for ABM joint design. To determine evaluation schemes and optimal designs, this paper provides a method for global optimization of joints that considers the integrated effects of multiple conditions, constructing a rapid and comprehensive solution for designing and evaluating key joints in the ABM.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":null,"pages":null},"PeriodicalIF":9.6,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142275783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Anomaly detection of cracks in synthetic masonry arch bridge point clouds using fast point feature histograms and PatchCore 使用快速点特征直方图和 PatchCore 对合成砖石拱桥点云中的裂缝进行异常检测

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2024-09-21 DOI: 10.1016/j.autcon.2024.105766

Yixiong Jing , Jia-Xing Zhong , Brian Sheil , Sinan Acikgoz

{"title":"Anomaly detection of cracks in synthetic masonry arch bridge point clouds using fast point feature histograms and PatchCore","authors":"Yixiong Jing , Jia-Xing Zhong , Brian Sheil , Sinan Acikgoz","doi":"10.1016/j.autcon.2024.105766","DOIUrl":"10.1016/j.autcon.2024.105766","url":null,"abstract":"<div><div>Management of ageing masonry arch bridges entails periodic site inspections to identify signs of potential structural degradation. Previous research has focused on detecting surface cracks from images. This paper develops an alternative approach where cracks are identified from point clouds via geometric distortions. An image-based anomaly detection method called <em>PatchCore</em> is customized for 3D applications for this purpose. First, Fast Point Feature Histograms (FPFH) are used to extract geometric features. Then <em>PatchCore</em> is applied on synthetic point clouds with crack labels, generated using 3D finite element modelling (FEM) and graphical modelling. Results show that the proposed method can capture surface and internal cracks in arches. Analyses show that the method is robust against measurement noise, initial damage and masonry surface roughness, and can be applied to other bridge components. Limitations of the method in detecting small changes in curvature and in-plane geometric distortions are highlighted for further improvements.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":null,"pages":null},"PeriodicalIF":9.6,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0926580524005028/pdfft?md5=220b25bd019c67b6d6dd33c4ba0141b7&pid=1-s2.0-S0926580524005028-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142275781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Human-centered intelligent construction for sustainable cities 以人为本的可持续城市智能建设

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2024-09-21 DOI: 10.1016/j.autcon.2024.105788

Hyuna Kang , Hakpyeong Kim , Juwon Hong , Jaewon Jeoung , Minhyun Lee , Taehoon Hong

{"title":"Human-centered intelligent construction for sustainable cities","authors":"Hyuna Kang , Hakpyeong Kim , Juwon Hong , Jaewon Jeoung , Minhyun Lee , Taehoon Hong","doi":"10.1016/j.autcon.2024.105788","DOIUrl":"10.1016/j.autcon.2024.105788","url":null,"abstract":"<div><div>Automatic technologies are a developing trend in the construction industry and have emerged by leveraging intelligent technologies. In automated construction, a human-centered approach to construction management is crucial as it improves productivity, safety, and sustainability by focusing on the needs of construction workers and building occupants. Therefore, focusing on sustainable construction, this paper explores technologies used in human-centered intelligent construction management (iCM) across building life cycle phases. Also, a new construction paradigm through a comprehensive review and outlines future research directions for human-centered iCM is introduced. It aims to provide practical and sustainable management solutions by integrating human-centered approaches in intelligent and automated construction technologies, offering valuable insights and guidance for practitioners and researchers. This paper highlights the importance of adopting a human-centered approach to meet the evolving challenges and demands of the iCM, along with the role of automation technologies in achieving these goals.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":null,"pages":null},"PeriodicalIF":9.6,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142275779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Tracking multiple construction workers using pose estimation and feature-assisted re-identification model 利用姿势估计和特征辅助再识别模式跟踪多个建筑工人

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2024-09-21 DOI: 10.1016/j.autcon.2024.105771

Nasrullah Khan , Syed Farhan Alam Zaidi , Muhammad Sibtain Abbas , Doyeop Lee , Dongmin Lee

{"title":"Tracking multiple construction workers using pose estimation and feature-assisted re-identification model","authors":"Nasrullah Khan , Syed Farhan Alam Zaidi , Muhammad Sibtain Abbas , Doyeop Lee , Dongmin Lee","doi":"10.1016/j.autcon.2024.105771","DOIUrl":"10.1016/j.autcon.2024.105771","url":null,"abstract":"<div><div>Tracking construction workers is crucial for ensuring worker safety, productivity, appropriate resource allocation, and regulatory compliance. However, when multiple workers resemble each other or temporary obstructions occur, maintaining accurate identification of individual workers with computer-vision-based tracking techniques is challenging. This paper proposes a multi-worker tracking framework comprising three key components: 1) a pose estimation model that localizes and generates keypoints for each worker, 2) a selective region algorithm with unique visual signatures and a re-identification (ReID) model that extracts features to distinguish workers, and 3) data association techniques that accurately track multiple workers simultaneously. The evaluation results obtained by using the higher-order tracking accuracy (HOTA) and multi-object tracking accuracy (MOTA) metrics on 16 annotated videos demonstrate the effectiveness of the framework. The selective region algorithm, combined with different configurations of trackers and ReID models, achieves an HOTA index of 85.83 % across various scenarios. This pre-emptive intermediation fosters multi-worker monitoring in dynamic construction environments.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":null,"pages":null},"PeriodicalIF":9.6,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142275782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Lightweight pruning model for road distress detection using unmanned aerial vehicles 利用无人驾驶飞行器进行道路状况检测的轻量级修剪模型

IF 9.6 1区工程技术

Automation in Construction Pub Date : 2024-09-21 DOI: 10.1016/j.autcon.2024.105789

Shengchuan Jiang , Hui Wang , Zhipeng Ning , Shenglin Li

引用次数: 0