Structural Control & Health Monitoring最新文献

{"title":"Vision-Based Multiscale Construction Object Detection under Limited Supervision","authors":"Yapeng Guo,&nbsp;Yang Xu,&nbsp;Hongtao Cui,&nbsp;Shunlong Li","doi":"10.1155/2024/1032674","DOIUrl":"10.1155/2024/1032674","url":null,"abstract":"<div>\u0000 <p>Contemporary multiscale construction object detection algorithms rely predominantly on fully-supervised deep learning, requiring arduous and time-consuming labeling process. This paper presents a novel semisupervised multiscale construction objects detection (SS-MCOD) by harnessing nearly infinite unlabeled images along with limited labels, achieving more accurate and robust detection results. SS-MCOD uses a deformable convolutional network (DCN)-based teacher-student joint learning framework. DCN uses deformable advantages to extract and fuse multiscale construction object features. The teacher module generates pseudolabels for construction objects in unlabeled images, while the student module learns the location and classification of construction objects in both labeled images and unlabeled images with pseudolabels. Experimental validation using commonly used construction datasets demonstrates the accuracy and generalization performance of SS-MCOD. This research can provide insights for other detection tasks with limited labels in the construction domain.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/1032674","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139962040","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}

{"title":"Fast Extraction Algorithm of Planar Targets Based on Point Cloud Data for Monitoring the Synchronization of Bridge Jacking Displacements","authors":"Dong Liang,&nbsp;Zeyu Zhang,&nbsp;Qiang Zhang,&nbsp;Erpeng Wu,&nbsp;Haibin Huang","doi":"10.1155/2024/9687805","DOIUrl":"10.1155/2024/9687805","url":null,"abstract":"<div>\u0000 <p>Transverse synchronization of vertical displacements of all jacking-up points is an important monitoring indicator to replace bearings in assembled multigirder bridges during the jacking phase. Currently, using target paper to identify the 3D coordinates of control points reduces the complexity of monitoring operations and improves the stability of data precision. However, the existing planar target locating methods have low accuracy, inefficiency, and subjectivity, which seriously hinders the construction process of bearing replacement. Accurately obtaining the center coordinates of multiple targets from a point cloud in a short monitoring period remains a challenge. This study proposes a high-precision automated algorithm to extract target center points in low-density point clouds to quickly calculate real target center points. First, we construct a standard point cloud model of the target papers for scanning, including color and geometric features. Then, we extract the measured point cloud of the typical jacking operation phase based on the reflection intensity and size information. Next, we map the intensity values of the measured point cloud into the color channel and register the measured point cloud with its standard point cloud model using the normal vector estimation and colored ICP algorithms. Finally, we extract the center point of the measured targets. Numerical experiments and engineering test results show that the proposed method converges quickly with high precision and good robustness, which saves 91.4% of the time compared with the traditional method. In general, this research can provide effective technical support for 3D laser scanning in monitoring the operation phase of bridge jacking.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/9687805","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139780357","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}

{"title":"DSNet: A Computer Vision-Based Detection and Corrosion Segmentation Network for Corroded Bolt Detection in Tunnel","authors":"Lei Tan,&nbsp;Xiaohan Chen,&nbsp;Dajun Yuan,&nbsp;Tao Tang","doi":"10.1155/2024/1898088","DOIUrl":"10.1155/2024/1898088","url":null,"abstract":"<div>\u0000 <p>Corroded bolt detection has been confirmed as a major issue in the structure health monitoring (SHM) of tunnels. However, detection-only methods will miss the corroded bolts, arising from the small rust area. In this study, the task is divided ingeniously into two parallel tasks, i.e., bolt detection and pixel-level rust segmentation, and the objective is fulfilled by taking the intersection of the two tasks, with the aim of enhancing the performance. To be specific, a detection and segmentation network (DSNet) is proposed based on multitask learning, leading to reduced false and missed detection rates. The coordinate attention module enhancing the focus of bolts in tunnel patches is incorporated in the detection branch, and the cross-stage partial-based decoder which can more accurately determine whether a pixel pertains to the corrosion area is employed in the segmentation branch. The mentioned branches share the same backbone to simplify the model. Sufficient comparisons and ablation experiments are performed to prove the superiority of the proposed algorithm based on the corroded bolt dataset captured from a real subway tunnel, which is publicly available in https://github.com/StreamHXX/Tunnel-lining-disease-image.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/1898088","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139781484","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}

{"title":"A Physics-Informed Neural Network for the Nonlinear Damage Identification in a Reinforced Concrete Bridge Pier Using Seismic Responses","authors":"Takahiro Yamaguchi,&nbsp;Tsukasa Mizutani","doi":"10.1155/2024/5532909","DOIUrl":"10.1155/2024/5532909","url":null,"abstract":"<div>\u0000 <p>The condition assessment of reinforced concrete (RC) bridge piers after an earthquake using measured responses is important for ensuring the safety of road and railway users. The problem is nonlinear, and the locations and extents of damages are various. However, previous research works focused on linear structural identification or model updating assuming a limited number of nonlinear materials for reasonable estimates. Leveraging the ability of deep learning (DL) for robustly estimating a large number of unknown parameters, this study proposes an ALL nonlinear spring multi-degree-of-freedom (MDOF) damage identification algorithm based on a physics-informed neural network (PINN). The algorithm is applied to a stacked bilinear rotational spring and damper model of a pier. The number of unknown parameters reaches about 50. The errors of estimated elastic stiffnesses, damping coefficients, and ductility factors (DFs) using simulated responses added with noises are 0.4%, 0.6%, and 3.1%, respectively. Using full-scale RC bridge pier shaking table experiments, the algorithm revealed the distributions of elastic stiffnesses and DFs along the pier height and their deteriorations. The effects of different types of local damages are quantitatively evaluated and visualized on the distributions.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/5532909","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139847573","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}

{"title":"System Identification of a Structure Equipped with a Cable-Bracing Inerter System Using Adaptive Extended Kalman Filter","authors":"Rui Zhang,&nbsp;Songtao Xue,&nbsp;Xinlei Ban,&nbsp;Ruifu Zhang,&nbsp;Liyu Xie","doi":"10.1155/2024/4930237","DOIUrl":"10.1155/2024/4930237","url":null,"abstract":"<div>\u0000 <p>An innovative cable-bracing inerter system (CBIS) has been proposed and shown to be effective in mitigating the structural response under dynamic excitation. The CBIS comprises an inerter element, an eddy current damping element, and a pair of tension-only cables that can transfer the story drift to rotating flywheels. To further investigate the characteristics of the CBIS, a system identification approach based on an adaptive extended Kalman filter (AEKF) and a recursive least-squares (RLS) algorithm is proposed. Depending on the CBIS model’s availability, the proposed approach uses two strategies: the AEKF identifies the parameters of the structure and the CBIS when the model is specific; alternatively, when the model is unspecific, the KF combined with an RLS algorithm identifies the restoring force generated by the CBIS as an unknown fictitious input. In addition, the AEKF incorporates a time-variant fading factor to track the target adaptively. The proposed approach is validated through free vibration and shaking table tests, demonstrating the accuracy in identifying structural parameters and restoring force provided by the CBIS. The identification process involves two stages: initially, the AEKF identifies the parameters of the bare structure without the CBIS, followed by a dual strategy using either AEKF or KF-RLS for identifying the parameters of the CBIS or its restoring force, respectively. The findings also verify the feasibility and validity of the mechanical model and operating principle of the CBIS, thereby contributing to the advancement and application of the CBIS in future studies.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/4930237","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139848023","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}

{"title":"Semiactive Control of Nonlinear Parametric Vibration of Super-Long Stay Cable in Cable-Stayed Bridge Installed with Magnetorheological Fluid Damper","authors":"Junping Du,&nbsp;Min Liu,&nbsp;Peng Zhou,&nbsp;Huigang Xiao","doi":"10.1155/2024/2161065","DOIUrl":"10.1155/2024/2161065","url":null,"abstract":"<div>\u0000 <p>As the stay cables of cable-stayed bridges become longer, parametric resonance with a large amplitude is more easily triggered, which becomes a vibration hazard of super-long stay cables. An increasing number of practical applications of vibration mitigation on stay cables demonstrate that vibration control strategies can effectively facilitate hazard mitigation and improve cable-stayed bridge reliability and service life. This study proposes a semiactive control approach to reduce the parametric vibration of super-long stay cables in cable-stayed bridges installed with magnetorheological fluid damper (MRFD). First, using the cable’s gravity sag curve equation, an equation governing the combined stay cable-bridge deck-damper control system was established to consider the effect of the chordwise force of cable gravity. Subsequently, a targeted LQR-based optimal active control law is proposed to provide the target control force in the semiactive control. The parametric influences on the performance of the LQR-based optimal active control were analysed to provide insight into the proposed control strategy. Since the semiactive control could achieve almost the same control efficacy of the targeted optimal active control, a semiactive control strategy employing MRFD is proposed to mitigate the parametric vibration of a super-long stay cable. Based on the proposed semiactive control strategy, the system was attached with the MRFD of the longest cable, S36, in the designed prototype long cable-stayed bridge. The efficacy of the established semiactive control system was also analysed. The analysis results confirm that the proposed semiactive control strategy and designed semiactive control system can perform similar to the LQR-based optimal active control. The semiactive control system attached to the MRFD can mitigate the parametric vibration of super-long stay cables in cable-stayed bridge engineering practice.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/2161065","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139858471","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}

{"title":"Autonomous Identification of Bridge Concrete Cracks Using Unmanned Aircraft Images and Improved Lightweight Deep Convolutional Networks","authors":"Fei Song,&nbsp;Ying Sun,&nbsp;Guixia Yuan","doi":"10.1155/2024/7857012","DOIUrl":"10.1155/2024/7857012","url":null,"abstract":"<div>\u0000 <p>The identification of the development of structural defects is an important part of bridge structure damage diagnosis, and cracks are considered the most typical and highly dangerous structural disease. However, existing deep learning-based methods are mostly aimed at the scene of concrete cracks, while they rarely focus on designing network architectures to improve the vision-based model performance from the perspective of unmanned aircraft system (UAS) inspection, which leads to a lack of specificity. Because of this, this study proposes a novel lightweight deep convolutional neural network-based crack pixel-level segmentation network for UAS-based inspection scenes. Firstly, the classical encoder-decoder architecture UNET is utilized as the base model for bridge structural crack identification, and the hourglass-shaped depthwise separable convolution is introduced to replace the traditional convolutional operation in the UNET model to reduce model parameters. Then, a kind of lightweight and efficient channel attention module is used to improve model feature fuzzy ability and segmentation accuracy. We conducted a series of experiments on bridge structural crack detection tasks by utilizing a long-span bridge as the research item. The experimental results show that the constructed method achieves an effective balance between reasoning accuracy and efficiency with the value of 97.62% precision, 97.23% recall, 97.42% accuracy, and 93.25% IOU on the bridge concrete crack datasets, which are significantly higher than those of other state-of-the-art baseline methods. It can be inferred that the application of hourglass-shaped depth-separable volumes can actively reduce basic model parameters. Moreover, the lightweight and efficient attention modules can achieve local cross-channel interaction without dimensionality reduction and improve the network segmentation performance.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/7857012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139803757","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}

{"title":"Pole-Placement-Based Calibration of an Electromagnetically Realizable Inerter-Based Vibration Absorber (IDVA) for Rotating Wind Turbine Blades","authors":"Zili Zhang,&nbsp;Xiang Li,&nbsp;Tobias Greve Larsen,&nbsp;Tao Sun,&nbsp;Qingshan Yang","doi":"10.1155/2024/7255774","DOIUrl":"10.1155/2024/7255774","url":null,"abstract":"<div>\u0000 <p>This paper deals with edgewise vibration mitigation of rotating wind turbine blades by means of inerter-based vibration absorber (IDVA), which can be realized both mechanically and electromagnetically. Introducing the electromagnetically-realizable IDVA to the blade forms a 3-degree-of-freedom (3-DOF) blade-IDVA system consisting of the rotating blade, an absorber, and a series inerter-dashpot-spring subsystem. Analytical optimal design formulas of the rotating blade-installed IDVA are then derived using a pole-placement method where the equal-modal-damping-ratio principle and the triple-root-bifurcation condition are applied. The analytical formulas show that the optimal parameters for the blade-IDVA system merely depend on the spinning speed of the rotor given the IDVA location and the absorber mass. Numerical results of the NREL 5 MW wind turbine with optimal IDVA show that optimal IDVA leads to superior performance than optimal TMD in mitigating the blade edgewise vibration and behaves nearly as same as optimal RIDTMD, along with slightly optimal damper parameters variation. This means that the inerter-dashpot-spring system can be deployed flexibly for damping edgewise vibrations of rotating blades.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/7255774","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139808689","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}

{"title":"A New Method for the Compaction Quality Inspection of High Rockfill Dams Based on 3D Laser Scanning Technology","authors":"Qiang Yao,&nbsp;Yu Wu,&nbsp;Jun He,&nbsp;Shunchao Qi,&nbsp;Hongtao Li","doi":"10.1155/2024/6662678","DOIUrl":"10.1155/2024/6662678","url":null,"abstract":"<div>\u0000 <p>The compaction quality is directly related to the deformation and stability of the rockfill dam. Measuring the test pit volume efficiently and accurately is the most critical step during the compaction quality inspection. A new method for calculating the test pit volume based on point cloud data is proposed. An auxiliary device that can change the scanning distance and angle of the handheld 3D laser scanner is developed to collect the initial point cloud. The segmentation method of the initial point cloud data including the test pit and the compaction surface outside the pit is to divide the data into two parts according to the order number of the segmentation point, after slicing and sorting point clouds, which is the key to ensuring the computational precision. The segmentation points are the adjacent two points with the greatest order number difference in these point clouds whose distance from the line connecting the end points of the slicing point clouds is less than <i>d</i>_<i>z</i>. The compaction surface point clouds are used to construct a plane by the least-squares algorithm so that the closed three-dimensional model is formed by registering it with the test pit point clouds. After converting the test pit surface to the horizontal plane by the Rodrigues formula, the test pit point clouds are divided into <i>n</i>² parts with equal projection areas on the horizontal plane, and <i>n</i>² prisms are constructed using them and their projection areas. The test pit volume is the sum of the intersection space volumes of all prisms and the test pit model, and the intersection space is determined by comparing the <i>Z</i>-values of point clouds. The new method was programmed in MATLAB and applied to the Shuangjiangkou rockfill dam with a height of 315 m. The relative error of volume results between the new method and the old water-filling method is 0.14–2.31%. The cause of the error is analyzed, and it is proved that the results of the new method are closer to the real volume of the test pit in theory. This method reduces the inspection cost but greatly improves the level of precision, efficiency, and intelligence for compaction quality inspection.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/6662678","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139808728","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}

{"title":"Quantum-Based Combinatorial Optimization for Optimal Sensor Placement in Civil Structures","authors":"Gabriel San Martín,&nbsp;Enrique López Droguett","doi":"10.1155/2024/6681342","DOIUrl":"https://doi.org/10.1155/2024/6681342","url":null,"abstract":"<div>\u0000 <p>Over the last decade, concepts such as industry 4.0 and the Internet of Things (IoT) have contributed to the increase in the availability and affordability of sensing technology. In this context, structural health monitoring (SHM) arises as an especially interesting field to integrate and develop these new sensing capabilities, given the criticality of structural application for human life and the elevated costs of manual monitoring. Due to the scale of structural systems, one of the main challenges when designing a modern monitoring system is the optimal sensor placement (OSP) problem. The OSP problem is combinatorial in nature, making its exact solution infeasible in most practical cases, usually requiring the use of metaheuristic optimization techniques. While approaches such as genetic algorithms (GAs) have been able to produce significant results in many practical case studies, their ability to scale up to more complex structures is still an area of open research. This study proposes a novel quantum-based combinatorial optimization approach to solve the OSP problem approximately, within the context of SHM. For this purpose, a quadratic unconstrained binary optimization (QUBO) model formulation is developed, taking as a starting point of the modal strain energy (MSE) of the structure. The framework is tested using numerical simulations of Warren truss bridges of varying scales. The results obtained using the proposed framework are compared against exhaustive search approaches to verify their performance. More importantly, a detailed discussion of the current limitations of the technology and the future paths of research in the area is presented to the reader.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/6681342","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141187654","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}