Structural Control & Health Monitoring最新文献_第6页

Output Only Damage Detection of a Steel Truss Bridge Based on a Semisupervised BiLSTM Modeling Scheme 基于半监督BiLSTM建模方案的钢桁架桥梁仅输出损伤检测

IF 4.6 2区工程技术

Structural Control & Health Monitoring Pub Date : 2025-05-22 DOI: 10.1155/stc/5965478

Tazwar Bakhtiyar Zahid, Shohel Rana, Md. Niamul Haque

{"title":"Output Only Damage Detection of a Steel Truss Bridge Based on a Semisupervised BiLSTM Modeling Scheme","authors":"Tazwar Bakhtiyar Zahid, Shohel Rana, Md. Niamul Haque","doi":"10.1155/stc/5965478","DOIUrl":"https://doi.org/10.1155/stc/5965478","url":null,"abstract":"<div>\u0000 <p>The application of machine learning techniques in bridge health monitoring is gaining widespread popularity as it overcomes the problems faced by conventional methods. However, the scarcity of labeled data for damaged bridges in training the model acts as a hindrance. The present study proposes a data science–based novel approach for overcoming this hindrance using a semisupervised, output-only method for multiple-level damage identification of a steel truss bridge. The method employs sequence-to-sequence modeling of vehicle-induced vibration response only from a single sensor position. The authors have used a bidirectional long short-term memory (BiLSTM) network for damage feature extraction. A statistical distance metric tool, Kullback–Leibler divergence, has then been utilized for feature discrimination. The method’s efficiency is numerically investigated through a 3-D finite element model of a steel truss bridge based on real bridge specifications. A dynamic analysis using a moving vehicle is performed to obtain vehicle-induced accelerations. A total of 36 different damage scenarios have then been incorporated into the bridge. The effect of sensor position and performance because of variation in vehicle operation has also been investigated. The results show that the proposed approach successfully detects all the damage scenarios. The methodology’s performance has also been validated in detecting damages for the Old ADA Bridge benchmark data. The methodology successfully detected multiple damage states using a single sensor response.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/5965478","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Application of Self-Diagnosis and Self-Repair on a Truss Prototype That Adapts to Loading Through Shape Morphing 自诊断自修复在形状变形适应荷载桁架原型上的应用

IF 4.6 2区工程技术

Structural Control & Health Monitoring Pub Date : 2025-05-21 DOI: 10.1155/stc/8827609

Arka P. Reksowardojo, Gennaro Senatore, Lucio Blandini, Ian F. C. Smith

{"title":"Application of Self-Diagnosis and Self-Repair on a Truss Prototype That Adapts to Loading Through Shape Morphing","authors":"Arka P. Reksowardojo, Gennaro Senatore, Lucio Blandini, Ian F. C. Smith","doi":"10.1155/stc/8827609","DOIUrl":"https://doi.org/10.1155/stc/8827609","url":null,"abstract":"<div>\u0000 <p>This paper presents experimental testing of self-diagnosis and self-repair strategies on an adaptive truss prototype that counteracts the effect of loading through shape morphing. The prototype is a simply supported spatial truss with a span of 6 m and is equipped with 12 linear actuators. The structure is designed to adapt to external loads through shape morphing—that is, by undergoing large shape changes to achieve configurations that are optimal for load-bearing. A damage event is replicated via the removal of a truss element, which simulates a loss of stiffness caused by buckling or fracture. A damage detection and localization algorithm is implemented based on the similarity evaluation of numerical and empirical redundancy matrices. Testing results demonstrate the efficacy of this method, with up to 81% and 79% accuracy for detection and localization, respectively, obtained considering all scenarios including false alarms (false positives) in the nondamaged state. For damaged states, the detection accuracy is 100% (no false negative). A self-repair strategy based on shape morphing is proposed. The structure is controlled into a shape that is optimal to carry the external load, achieving a significant stress redistribution to mitigate the effect of damage. Experimental results demonstrate that when an element of the structure is removed to simulate damage, the stress increases by up to 22% compared to the undamaged condition. This increase is fully recovered through shape adaptation. Actuator faults were also analyzed. With all actuators in operation, shape adaptation reduces stress by up to 22% under peak load (in the absence of damage). When two actuators are simulated as faulty, a stress reduction of up to 11% is still achieved, demonstrating the effectiveness of the proposed shape morphing–based control strategy.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/8827609","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144108855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Active Learning–Enhanced Ensemble Method for Spatiotemporal Correlation Modeling of Neighboring Bridge Behaviors to Girder Overturning 基于主动学习增强的相邻桥梁倾覆行为时空关联建模集成方法

IF 4.6 2区工程技术

Structural Control & Health Monitoring Pub Date : 2025-05-12 DOI: 10.1155/stc/6047080

Ru An, Mengjin Sun, You Dong, Lu Guo, Lei Jia, Xiaoming Lei

{"title":"Active Learning–Enhanced Ensemble Method for Spatiotemporal Correlation Modeling of Neighboring Bridge Behaviors to Girder Overturning","authors":"Ru An, Mengjin Sun, You Dong, Lu Guo, Lei Jia, Xiaoming Lei","doi":"10.1155/stc/6047080","DOIUrl":"https://doi.org/10.1155/stc/6047080","url":null,"abstract":"<div>\u0000 <p>Structural health monitoring (SHM) systems are widely deployed in transportation networks, yet traditional methods often focus on individual bridges, overlooking interdependencies between neighboring structures. This study proposes an active learning–enhanced ensemble learning model to predict the tilt behavior of adjacent bridges by leveraging critical response data from multiple bridges. The ensemble model integrates gradient boosting, random forest, and Gaussian process regressors, providing both predictive means and uncertainty quantification. Active learning iteratively selects the most informative samples, improving model efficiency and reducing data requirements. The model accurately predicts vertical displacement and tilt using responses from neighboring bridges, effectively capturing spatiotemporal correlations and dynamic interactions. Active learning achieves comparable accuracy with just 50% of traditional training samples, demonstrating its efficiency. The results reveal structural interdependencies influenced by stiffness and load distribution variations. The successful prediction of tilt behavior underscores the model’s potential for real-time SHM, early overturning warnings, and enhanced bridge safety.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/6047080","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143939418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

An Energy Framework to Control Viscoelastic Semi-Active Devices in Plan-Wise One-Way Asymmetric Systems 平面单向非对称系统粘弹性半主动装置控制的能量框架

IF 4.6 2区工程技术

Structural Control & Health Monitoring Pub Date : 2025-05-08 DOI: 10.1155/stc/7091316

M. De Iuliis, E. Miceli, P. Castaldo

{"title":"An Energy Framework to Control Viscoelastic Semi-Active Devices in Plan-Wise One-Way Asymmetric Systems","authors":"M. De Iuliis, E. Miceli, P. Castaldo","doi":"10.1155/stc/7091316","DOIUrl":"https://doi.org/10.1155/stc/7091316","url":null,"abstract":"<div>\u0000 <p>This study proposes new strategies for the semi-active control of the dynamic response of a plan-wise asymmetrical structural system using viscoelastic devices. Different from some literature proposals, these innovative strategies are designed to be immediately interpretable, aiming to optimize the different terms of the energy balance equation through a set of closed-form analytical control algorithms to manage the properties of semi-active devices. Specifically, four algorithms have been developed to maximize the energy dissipated by the system or minimize the elastic energy, kinetic energy, and input energy. These algorithms have been tested through an extensive numerical investigation by modifying the main structural parameters of the asymmetrical system and considering 85 accelerometric input signals with different dynamic characteristics related to both far-field and near-fault records. The effectiveness of the four proposed strategies, aimed to modify the semi-active device properties, was evaluated by comparing the seismic responses of asymmetric systems, in terms of both relative displacement and energy components, with the regular configuration of semi-active devices (i.e., passive control) and other algorithms, such as “Kamagata & Kobori” and “sky hook” finalized, respectively, to manage stiffness and damping extra-structural resources. The results demonstrated the effectiveness of the proposed strategies, especially, in the presence of flexible systems and high-demanding near-fault seismic events.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/7091316","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143926030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Bolt Looseness Quantitative Visual Detection With Cross-Modal Fusion 基于跨模态融合的螺栓松动定量视觉检测

IF 4.6 2区工程技术

Structural Control & Health Monitoring Pub Date : 2025-05-06 DOI: 10.1155/stc/2282684

Zhipeng Wang, Jiajun Ma, Gui Xue, Feida Gu, Ruochen Ren, Yanmin Zhou, Bin He

{"title":"Bolt Looseness Quantitative Visual Detection With Cross-Modal Fusion","authors":"Zhipeng Wang, Jiajun Ma, Gui Xue, Feida Gu, Ruochen Ren, Yanmin Zhou, Bin He","doi":"10.1155/stc/2282684","DOIUrl":"https://doi.org/10.1155/stc/2282684","url":null,"abstract":"<div>\u0000 <p>Intelligent bolt looseness detection systems offer significant potential for accurately promptly detecting bolt looseness. Bolt looseness detection in high-speed train undercarriages is challenging due to the low-texture surfaces of structural parts and variations of illumination and viewpoint in typical maintenance scenes. These factors hinder the quantification detection of bolt looseness using traditional 2D visual inspection methods. In this paper, we present a cross-modal fusion-based method for the quantification detection of bolt looseness in high-speed train undercarriages. We propose a cross-modal fusion approach using a cross-modal transformer, which integrates 2D images and 3D point clouds to improve adaptability to varying illumination conditions in maintenance scenes. To address geometric projection distortions caused by varying-view perspective transformations, we use the height difference between the bolt cap and the fastening plane in point clouds as the criterion for bolt loosening. The experimental results indicate that the proposed method outperforms the base-line on our dataset of 5823 annotated RGB-D images from a locomotive depot, achieving an average measurement error of 0.39 mm.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/2282684","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143908969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Efficient Measurement of Structural Defect Depth Using Parallel Laser Line-Camera System 利用平行激光线相机系统有效测量结构缺陷深度

IF 4.6 2区工程技术

Structural Control & Health Monitoring Pub Date : 2025-04-29 DOI: 10.1155/stc/1599724

Chaobin Li, R. K. L. Su

{"title":"Efficient Measurement of Structural Defect Depth Using Parallel Laser Line-Camera System","authors":"Chaobin Li, R. K. L. Su","doi":"10.1155/stc/1599724","DOIUrl":"https://doi.org/10.1155/stc/1599724","url":null,"abstract":"<div>\u0000 <p>The precise depth measurement of common structural defects, such as bulging, delamination, and spalling, is paramount in building condition assessment. This paper presents an efficient and portable parallel laser line-camera system designed for accurately reconstructing defect depth profiles from projected laser stripes. The system features a telescopic design to enhance the measurement range and operational flexibility. Central to its efficacy is a machine learning–aided image processing algorithm that facilitates both robust and highly accurate depth measurements. Specifically, advanced deep learning techniques are applied to detect and segment laser stripes from background interference. A novel hypothesis optimization (HO) algorithm, grounded in a three-layer backpropagation (BP) neural network, is proposed to reduce errors in laser baseline recovery caused by image distortion further. Comprehensive laboratory and field experiments validate the measurement accuracy and superior noise suppression capabilities of the system. Additionally, the paper studies potential errors that could emerge during field operations, thereby confirming the practical utility of the device. The proposed system quickly generates surface profiles in a single shot, making it a valuable tool for monitoring uneven objects.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/1599724","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143884239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Numerical and Experimental Analysis of Multifrequency Composite Synchronization of Four Motors in a Vibrating System With the Modified Fuzzy Adaptive Sliding Model Controlling Method 基于改进模糊自适应滑模控制方法的振动系统四电机多频复合同步的数值与实验分析

IF 4.6 2区工程技术

Structural Control & Health Monitoring Pub Date : 2025-04-28 DOI: 10.1155/stc/9920013

Lei Jia, Qingsong Chang, Yang Tian, Xin Zhang, Ziliang Liu

{"title":"Numerical and Experimental Analysis of Multifrequency Composite Synchronization of Four Motors in a Vibrating System With the Modified Fuzzy Adaptive Sliding Model Controlling Method","authors":"Lei Jia, Qingsong Chang, Yang Tian, Xin Zhang, Ziliang Liu","doi":"10.1155/stc/9920013","DOIUrl":"https://doi.org/10.1155/stc/9920013","url":null,"abstract":"<div>\u0000 <p>This article addresses the multifrequency composite synchronization of four motors within a vibrating system. Multifrequency synchronization is commonly utilized in engineering due to its effectiveness in screening mixed materials of varying shapes and stickiness. The frequency ratio parameter <i>n</i> influences both the efficiency of the screening process and the overall screening results. Although multifrequency self-synchronization motion can be realized, it can only be realized for integer frequency doubling (<i>n</i> = 2 and <i>n</i> = 3), which limits the diversity of material screening types. By introducing the multifrequency controlled synchronization method, the multifrequency synchronization with noninteger frequencies (<i>n</i> = 1.1–1.9) can be realized, which requires much cost on electrical equipment. To solve this problem, the multifrequency composite synchronization method in this article is proposed. The electromechanical coupling dynamics model of the vibration system is constructed by the Lagrange energy equation. Then, the synchronous condition and stability criteria are derived via the multiscale method by combining the speeds with phase differences. A novel fuzzy adaptive sliding model controlling method associated with a master–slave controlling strategy is introduced to realize multifrequency composite synchronization. The results show that speed errors in different frequencies are only 1000% and 3000%, respectively, and the swing response of the vibration system is small. It presents that the vibration system can not only realize the material screening stably and effectively but also reduce the cost of electrical equipment. The proposed method provides a new reference for multifrequency screening equipment.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/9920013","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143880162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Automatic Identification of Diverse Tunnel Threats With Machine Learning–Based Distributed Acoustic Sensing 基于机器学习的分布式声传感隧道威胁自动识别

IF 4.6 2区工程技术

Structural Control & Health Monitoring Pub Date : 2025-04-28 DOI: 10.1155/stc/9780866

Taiyin Zhang, Cheng-Cheng Zhang, Tao Xie, Xiaomin Xu, Bin Shi

{"title":"Automatic Identification of Diverse Tunnel Threats With Machine Learning–Based Distributed Acoustic Sensing","authors":"Taiyin Zhang, Cheng-Cheng Zhang, Tao Xie, Xiaomin Xu, Bin Shi","doi":"10.1155/stc/9780866","DOIUrl":"https://doi.org/10.1155/stc/9780866","url":null,"abstract":"<div>\u0000 <p>As the backbone of modern urban underground traffic space, tunnels are increasingly threatened by natural disasters and anthropogenic activities. Current tunnel surveillance systems often rely on labor-intensive surveys or techniques that only target specific tunnel events. Here, we present an automated tunnel monitoring system that integrates distributed acoustic sensing (DAS) technology with ensemble learning. We develop a fiber-optic vibroacoustic dataset of tunnel disturbance events and embed vibroscape data into a common feature space capable of describing diverse tunnel threats. On the scale of seconds, our anomaly detection pipeline and data-driven stacking ensemble learning model enable automatically identifying nine types of anomalous events with high accuracy. The efficacy of this intelligent monitoring system is demonstrated through its application in a real-world tunnel, where it successfully detected a low-energy but dangerous water leakage event. The highly generalizable machine learning model, combined with a universal feature set and advanced sensing technology, offers a promising solution for the autonomous monitoring of tunnels and other underground spaces.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/9780866","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143880161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

A Bridge Crack Detection and Localization Approach for Unmanned Aerial Systems Using Adapted YOLOX and UWB Sensors 基于YOLOX和UWB传感器的无人机系统桥梁裂缝检测与定位方法

IF 4.6 2区工程技术

Structural Control & Health Monitoring Pub Date : 2025-04-23 DOI: 10.1155/stc/3621939

Mida Cui, Yujie Yan, Dongming Feng, Gang Wu, Zewen Zhu

{"title":"A Bridge Crack Detection and Localization Approach for Unmanned Aerial Systems Using Adapted YOLOX and UWB Sensors","authors":"Mida Cui, Yujie Yan, Dongming Feng, Gang Wu, Zewen Zhu","doi":"10.1155/stc/3621939","DOIUrl":"https://doi.org/10.1155/stc/3621939","url":null,"abstract":"<div>\u0000 <p>The management and maintenance of the aging bridges can benefit from an efficient and automatous bridge inspection process, such as crack detection and localization. This paper presents a robust and efficient approach for unmanned aerial vehicle (UAV)-based crack recognition and localization. An adapted YOLOX model is used in the proposed approach to improve accuracy and efficiency of crack recognition, and hence to enable real-time crack recognition from the captured UAV images at the edge-computing devices. In this way, non-crack images can be recognized in real-time during data acquisition and be filtered out to relieve the burden of subsequent data recording. In addition, a self-organizing positioning system based on ultra-wide-band (UWB) sensors is employed in the proposed system to enable real-time UAV positioning and crack localization in GNSS-denied areas such as spaces underneath the bridge deck. Experiment studies were carried out to investigate the impact of the quantities of employed UWB base stations on the UAV positioning accuracy. Finally, the proposed approach is tested on a self-developed UAV system and the effectiveness is validated through laboratory tests and real-world field tests.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/3621939","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143861781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

An Advanced Computer Vision Method for Noncontact Vibration Measurement of Cables in Cable-Stayed Bridges 用于斜拉桥电缆非接触振动测量的先进计算机视觉方法

IF 4.6 2区工程技术

Structural Control & Health Monitoring Pub Date : 2025-04-23 DOI: 10.1155/stc/1254049

Naiwei Lu, Weiming Zeng, Jian Cui, Yuan Luo, Xiaofan Liu, Yang Liu

{"title":"An Advanced Computer Vision Method for Noncontact Vibration Measurement of Cables in Cable-Stayed Bridges","authors":"Naiwei Lu, Weiming Zeng, Jian Cui, Yuan Luo, Xiaofan Liu, Yang Liu","doi":"10.1155/stc/1254049","DOIUrl":"https://doi.org/10.1155/stc/1254049","url":null,"abstract":"<div>\u0000 <p>With the development of computer and image processing technologies, computer vision (CV) has been attracting increasing attention in the field of civil engineering measurement and monitoring. Cables in slender structures have unique challenges for CV-based vibration measurement methods, such as low pixel proportion and sensitivity to environmental conditions. This study proposes a noncontact vibration measurement method based on a line tracking algorithm (LTA). The robustness and applicability of the proposed method under varying image resolutions, signal-to-noise ratios, and cable inclination angles were systematically evaluated through experimental test of a cable specimen. To validate the effectiveness of the proposed method for practical detection applications, a vibration test on a scaled cable-stayed bridge model was carried out. The numerical result indicates that the LTA provides high reliability and accuracy values of the cable force. The maximum errors of the first-order self-vibration frequency and cable force of the scaled cable-stayed bridge is 0.99% and 2%, respectively. The proposed method maintains strong stability across various conditions, which provides a reference for long-term structural health monitoring of cable-stayed bridges.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/1254049","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143866016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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