Structural Control & Health Monitoring最新文献

{"title":"Analytical Model and Abnormality Detection of the Fluid Viscous Damper in Railway Suspension Bridges Considering Performance Change","authors":"Shangtao Hu,&nbsp;Dongliang Meng,&nbsp;Hong Hao","doi":"10.1155/stc/2221608","DOIUrl":"https://doi.org/10.1155/stc/2221608","url":null,"abstract":"<div>\u0000 <p>Fluid viscous dampers (FVDs) in long-span bridges are prone to performance change, in which the gap effect caused by oil leakage and the parameter alteration induced by viscous material denaturation are two primary sources of change. These variations may negatively affect the safety of both the bridge and the damper, thus underlining the significance of performance assessment and abnormality detection. This study develops a Gap-Maxwell (G-M) model to simulate the restoring force characteristics of the FVD considering performance alteration and subsequently suggests identification methods for gap and parameter change to capture the condition variation of the damper. The G-M model contains a gap–hook element group and a Maxwell element, where the gap length of the gap element represents the leakage, and the parameter change is achieved by setting different parameter values for the Maxwell element. Its feasibility is verified by comparison with the cyclic test results. The simplified longitudinal movement pattern for the railway suspension bridge during the operational stage is suggested. Based on the G-M model and the movement pattern, the segmental gap identification (SGI) method is proposed to determine the gap length by segmenting the original data and identifying the gap in each segment. Numerical simulations illustrate its accuracy and robustness under different damper parameter settings and noise pollution. The G-M model parameter identification (GMPI) procedure is raised to capture the parameter change, which follows a procedure of preprocessing, clustering, fitting, and optimization. It is numerically proved to be effective in identifying the damping coefficient and velocity exponent of the FVD.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/2221608","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143513742","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":"An Attention-Based Detection Method of Fatigue Cracks on Steel","authors":"Qian-Qian Yu,&nbsp;Jie Wang,&nbsp;Xiang-Lin Gu,&nbsp;Sudao He,&nbsp;Shenghan Zhang","doi":"10.1155/stc/7487687","DOIUrl":"https://doi.org/10.1155/stc/7487687","url":null,"abstract":"<div>\u0000 <p>Steel structures are susceptible to fatigue cracking under cyclic loading, which can lead to catastrophic structural failure. In the incipient phase of crack propagation, the width of fatigue cracks typically measures less than 0.1 mm, making them difficult to detect using standard imaging techniques. This study presents a novel approach to crack detection on steel structures by tracking the displacement field on the structural surface derived from visual data. Initially, video or sequential images of the target structure under loading are captured and processed using an enhanced dense feature-matching model. The surface displacement field is then computed from the coordinate difference of the numerous matched feature points. By extracting discontinuities within the displacement field, fatigue cracks can be localized. Two case studies were conducted to validate the methodology: one involving a with a pre-existing crack and another steel plate with fatigue crack propagation. The findings indicate that the proposed method can be used to detect minuscule cracks, with crack widths as small as 5 μm. Factors potentially influcencing the method, including the texture of the steel surface, the region of interest (ROI) area ratio, the density of matching, and the resolution of input images, were discussed. Compared to traditional image-based semantic segmentation techniques, this approach is more convenient and precise, offering a promising avenue for the nondestructive evaluation of steel structures in civil engineering.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/7487687","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143497065","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":"Damage Localization at Steel–Concrete Interface Using Nonlinear Ultrasonic Time Reversal Method","authors":"Yi Wen,&nbsp;Linsheng Huo,&nbsp;Nan Zhao,&nbsp;Hongnan Li","doi":"10.1155/stc/8868516","DOIUrl":"https://doi.org/10.1155/stc/8868516","url":null,"abstract":"<div>\u0000 <p>Steel–concrete composite structures are prevalent in civil engineering, however, due to the temperature variation and fatigue loading, the interface between the steel tube and the core concrete is susceptible to various types of damage, including cracking, delamination, and debonding. Accurate localization of interface damage is crucial to ensure the safety of steel–concrete composite structures. The time-reversal (TR) method is commonly used in nondestructive testing for localizing structural linear damage due to its temporal and spatial focusing characteristics. However, the damage in the steel-concrete interface exhibits complex mechanical behavior and results in localization errors with the traditional TR method. To address this challenge, combined with the advantages of the VAM method, this paper proposes a nonlinear ultrasonic TR method to improve the accuracy of the TR method. This novel approach involves simultaneously exciting low-frequency (LF) and high-frequency (HF) signals using only one lead zirconate titanate (PZT) transducer, extracting the first-order modulation sideband signal, reversing and reemitting this signal, and utilizing the focused signal image to determine the location of damage at the interface. To validate the effectiveness of the proposed method, experiments were conducted on a concrete-filled steel tube with prefabricated interface damage to check its localization accuracy. The results clearly demonstrate an improvement in localization accuracy when using the proposed method compared to the conventional TR method. Specifically, the relative error in the coordinates for damage determined by the conventional TR method was significantly reduced from (25.89%, 18.82%) to (3.53%, 7.06%) with the proposed method. These findings underscore the superior performance of the proposed nonlinear ultrasonic TR method in localizing damage at the steel-concrete interface.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/8868516","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143475738","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":"Identification and Localization of Structural Damage Using the Second-Largest Eigenvalue of the Mutative-Scale Symbolic Matrix as the Damage Indicator","authors":"Shuang Meng,&nbsp;Dongsheng Li,&nbsp;Xiaoyu Bai","doi":"10.1155/stc/2484661","DOIUrl":"https://doi.org/10.1155/stc/2484661","url":null,"abstract":"<div>\u0000 <p>Time series–related methods in structural damage detection have gained increasing recognition due to their effectiveness, yet they face limitations in accuracy and efficiency for data processing, particularly in damage localization. In this study, we propose a novel method that utilizes a mutative-scale symbolic matrix, which extracts the second-largest eigenvalue as a damage indicator, to address the difficult problems of damage detection under random excitation. Unlike the conventional symbolized time series method, the mutative-scale symbolic matrix method selects data from the virtual impulse response function series at specific intervals, based on the Pearson correlation coefficient, and uses these data with the intervals to construct the mutative-scale symbolic matrix through joint occurrence entropy. The second-largest eigenvalue of the matrix is identified as an effective damage indicator which significantly magnifies the variations in structural characteristics. Damage localization is achieved by exploring damage occurrence between different reference and measurement points, and the flexibility in selecting these points enables a more precise determination of the damaged area according to the technology process based on dichotomy. A 10-DOF numerical model subjected to random Gaussian white noise is initially employed to validate the accuracy of the damage indicator for damage identification and localization. Subsequently, upon experimental application to a testbed structure, the proposed method exhibited super robustness in data selection under different damage types, with higher computational efficiency than conventional methods.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/2484661","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143466245","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":"Active Vibration Isolation Platforms for Wafer Front Opening Unified Pod Transporting Carts Under Raised Floor Irregularities in Industrial Factories","authors":"Chien-Liang Lee,&nbsp;Yung-Tsang Chen,&nbsp;Yen-Po Wang,&nbsp;Lap-Loi Chung,&nbsp;Meng-Chieh Liu,&nbsp;Li-Yen Lu","doi":"10.1155/stc/2134915","DOIUrl":"https://doi.org/10.1155/stc/2134915","url":null,"abstract":"<div>\u0000 <p>This study was conducted to examine the vibration control performance of the active isolation platform (AIP) implemented on the cart table (CT) of a moving front opening unified pod (FOUP) transporting cart to prevent damage to fragile silicon wafers during transportation across different buildings in semiconductor fabs. Additionally, the equation of motion for the proposed AIP–cart system simulated by a full vehicle model under raised floor irregularities was derived. Moreover, the direct output feedback control algorithm was used to determine the optimal feedback gain matrix for calculating the active control forces of the AIP. Furthermore, the dynamic time histories of the proposed model under raised floor irregularities were analyzed by the discrete–time state–space procedure (SSP), and the numerical simulation results revealed that AIP effectively suppressed the bouncing (or vertical) acceleration with a reduction of &gt; 90% at FOUP locations to 2.37 m/s² (&lt; 9.81 m/s² or 1.0 g, the bouncing acceleration threshold) to prevent FOUPs (or fragile silicon wafers) from bouncing away from the CT without AIP, causing damages to the wafers via collisions. Moreover, AIP greatly reduced the pitching angular rotation with a reduction of &gt; 65% to prevent the sliding of FOUP-stored wafers from the supporting slots inside FOUPs when the FOUP-transporting cart traversed through a larger bump between the expansion joints. The flexible AIP that demanded less control force (27.08 N) significantly isolated the high-frequency response transmitted from the CT and effectively enhanced its damping ratio to suppress the resonance low-frequency response induced by intermittent perforated floor irregularities or bumps. From a practical point of view, the proposed AIP scheme implemented on CT can be adopted for protecting jumping- or sliding-induced collision damages to wafers (or similar fragile products) transported by carts to reduce huge economic losses in industry.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/2134915","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143439109","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 Novel Nonlinear Output-Only Damage Detection Method Based on the Prediction Error of PCA Euclidean Distances Under Environmental and Operational Variations","authors":"Jiezhong Huang,&nbsp;Sijie Yuan,&nbsp;Dongsheng Li,&nbsp;Tao Jiang","doi":"10.1155/stc/4684985","DOIUrl":"https://doi.org/10.1155/stc/4684985","url":null,"abstract":"<div>\u0000 <p>Vibration-based damage detection relies on changes in structural dynamic features. However, environmental and operational variations (EOVs) can cause changes in dynamic features that mask those caused by damage. In addition, the EOV effects on dynamic features are often nonlinear, which limits the application of many linear damage detection methods. A novel nonlinear output-only method is proposed to address this. This method leverages variational mode decomposition (VMD) as a preprocessing step to remove seasonal patterns and noise from the modal frequencies. The first modes of the decomposition results (IMF1 signals) are then used to calculate the Euclidean distance based on the residual obtained by the principal component analysis (PCA) method. To eliminate the nonlinear EOV effects and provide normalized damage features for reliable continuous dynamic monitoring, a Gaussian process regression (GPR) model is trained to learn the underlying calculation rule of the PCA Euclidean distance. Due to the linear nature of PCA, the nonlinear EOV effects are still retained in both the PCA Euclidean distance and the GPR–predicted value. Through a subtraction process, their common nonlinear environmental effects can be removed, and the resulting prediction error can serve as a normalized feature sensitive to structural damage. The proposed method is validated through a simulated 7-DOF example and real data from the Z24 bridge, with several comparisons highlighting its effectiveness.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/4684985","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143438897","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":"Domain Knowledge Embedded InSAR-Based 3D Displacement Monitoring of Urban Buildings","authors":"Ya-Nan Du,&nbsp;De-Cheng Feng,&nbsp;Gang Wu","doi":"10.1155/stc/8864614","DOIUrl":"https://doi.org/10.1155/stc/8864614","url":null,"abstract":"<div>\u0000 <p>Continuous monitoring of building displacement is crucial for urban structural safety. While traditional methods are costly, Interferometric Synthetic Aperture Radar (InSAR) offers a cost-effective alternative, providing long-term displacement data. However, due to the insensitivity of SAR radar to north-south displacement, using InSAR alone can only measure settlement and east-west displacement. To address this limitation, this paper presents a three-dimensional (3D) deformation extraction model. The model embeds domain knowledge to introduce additional constraints, which are then used to establish the relationship between north-south and east-west displacement. This relationship allows for the extraction of 3D displacement of buildings from the line of sight (LOS) displacement measured by InSAR. This model was applied to Tower 2 of Yingli International Financial Center (YIFC) in Chongqing, China, and the 3D displacement of the building between 2018 and 2021 was obtained.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/8864614","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143431575","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":"Estimation of Bridge Girder Cumulative Displacement for Component Operational Warning Using Bayesian Neural Networks","authors":"Xiaoming Lei,&nbsp;Zhen Sun,&nbsp;Ao Wang,&nbsp;Tong Guo,&nbsp;Tomonori Nagayama","doi":"10.1155/stc/9974584","DOIUrl":"https://doi.org/10.1155/stc/9974584","url":null,"abstract":"<div>\u0000 <p>The main girders of suspension bridges experience significant deformation due to temperature variations, wind dynamics, and vehicle loads, causing movement at the girder ends and friction among components such as bearings, expansion joints, and viscous dampers. Early warning of the component anomaly is vital for preventive maintenance. This paper develops a two-stage framework for predicting girder end displacement to facilitate anomaly detection. First, a Bayesian neural network is employed to predict girder end cumulative displacement, accounting for uncertainties inherent in the prediction process. Second, an anomaly detection algorithm utilizing a Mahalanobis distance–based approach is implemented to provide warnings to operations based on both measured and predicted data. The effectiveness of the proposed approach is validated using data collected from multiple loads and displacement responses of a suspension bridge. The analysis reveals that the GEV distribution is highly proficient in capturing the underlying pattern of the cumulative displacement indicator, enabling the establishment of an appropriate threshold. This method proves successful in identifying anomalies in critical components such as viscous dampers, enhancing predictive and preventive maintenance practices and contributing to the longevity and safety of bridge infrastructure.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/9974584","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143424039","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":"Using Deep Learning to Estimate Vibration Comfort of Large-Scale Shake Table During Operation","authors":"Minte Zhang,&nbsp;Tong Guo,&nbsp;Yueran Zong,&nbsp;Weijie Xu,&nbsp;Chee Kiong Soh","doi":"10.1155/stc/6888254","DOIUrl":"https://doi.org/10.1155/stc/6888254","url":null,"abstract":"<div>\u0000 <p>Shake tables are useful earthquake simulation tools for structural seismic experiment, but they may also inadvertently induce vibrations to nearby buildings while in operation. Accelerating the comfort level quantification process of these vibrations before conducting a shake table test is necessary. To this end, this paper focuses on the influence of vibration introduced by a 6 × 9 m large-scale shake table at Southeast University and presents a one-dimensional convolutional neural network–based deep learning approach to efficiently estimate the vibration comfort of the shake table laboratory and surrounding buildings. Based on the on-site structural vibration monitoring of shake table test, a three-dimensional numerical model of the shake table–soil–surrounding building system is established and validated through the finite element method, and thus a dataset comprising 12,215 groups of input (i.e., peak acceleration values and time-history of the triaxial ground motion) and output (i.e., three-directional acceleration response for nine measuring points of surrounding buildings) data is simulated. Thereafter, the deep learning network is trained with 80% of the dataset and tested with the remaining 20%. The test results indicate that the approach enables the network to directly extract dynamic features from triaxial ground motion accelerations and to accurately estimate the weighted acceleration level (WAL) of nine different locations at the surrounding buildings. Finally, the optimized network is verified through an actual shake table experimental test on a self-centering concrete structure, which confirms the superior performance of the proposed approach on shake table–induced vibration comfort estimation. The approach is also beneficial for researchers to design reasonable loading scenarios before conducting shake table tests.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/6888254","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143396997","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":"Monitoring-Based Evaluation of Wind-Induced Vibration and Travel Comfort of Long-Span Suspension Bridge","authors":"Zhongxiang Liu,&nbsp;Haojun Cai,&nbsp;Tong Guo,&nbsp;Xingwang Liu,&nbsp;Yongtao Bai,&nbsp;Chunxu Qu","doi":"10.1155/stc/9962003","DOIUrl":"https://doi.org/10.1155/stc/9962003","url":null,"abstract":"<div>\u0000 <p>In this paper, evaluation of wind-induced vibration and travel comfort of the long-span suspension bridge were comprehensively conducted based on multisource monitoring data. The wind field distribution and turbulent characteristics during the normal and vortex-induced vibration (VIV) period were comparatively revealed. It reveals that the bridge experienced vertical VIV due to the long-duration wind with specific speed perpendicularly acting on the girder, which cannot be predicted by the turbulence intensity and gust factor. Meanwhile, dynamic response evolution, VIV lock-in effect, modal identification, and wavelet spectrum were further explored based on displacement and acceleration. The VIV frequency was consistent with a natural frequency of the bridge, whose mode can been determined by the deflection correlation heat map. The VIV was due to periodic vortex shedding generate aerodynamic forces, and the reaction of the structure vibration on vortex shedding can cause the vortex shedding frequency to be “locked” over a considerable range of wind speeds. According to driving visual safety and vibration tolerance, it is indicated that such VIV of the bridge may lead to the very discomfort for driving and pedestrian can tolerate short-term vibration in this period. Comfort evaluation for the bridge during the VIV should be further improved accuracy and reliability, which can contribute to emergency response to VIV situations. Note that a certain degree of discomfort may occur under normal vibration conditions, which raises doubts about the reasonableness of the limit value.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/9962003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388957","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}