Recent studies have demonstrated that inerter‐based dampers exhibit superior performance in mitigating cable vibration over conventional passive viscous dampers (VDs). This paper develops a new inerter‐based damper called the eddy‐current inertial mass damper (ECIMD), which consists of a rotary eddy‐current damping element and a paralleled ball screw inertial mass element. Inspired by the advantages of two VDs on a single stay cable, the damping of a stay cable with two ECIMDs, either at opposite cable ends or the same cable end, was investigated through theoretical analysis, experimental study, and parameter optimization. First, the mechanical model of the ECIMD was derived from the geometrical configuration, and its effectiveness was verified through mechanical performance tests on two ECIMD prototypes. Subsequently, theoretical analysis models of the cable‐ECIMD system were established by considering the cable sag, flexural stiffness, and boundary conditions. Furthermore, control performances of a model cable attached with two ECIMDs were experimentally evaluated. Finally, the multimode damping effect of two ECIMDs at the same cable end was highlighted through parameter optimization. Results show that when two ECIMDs are installed at opposite cable ends, the coupled single‐mode damping effect of two ECIMDs is approximately the sum of individual contributions from each ECIMD. When mechanical properties of two ECIMDs at the same cable end can match well with each other, the coupled single‐mode and multimode damping effect of two ECIMDs can be significantly enhanced compared with that of a single ECIMD installed at a further distance away from the cable anchorage.
{"title":"Damping of a stay cable with two eddy‐current inertial mass dampers: Theoretical analysis, experimental study, and parameter optimization","authors":"Zhihao Wang, Zhipeng Cheng, Hao Wang, Fangfang Yue, Hui Gao, Buqiao Fan","doi":"10.1002/stc.3085","DOIUrl":"https://doi.org/10.1002/stc.3085","url":null,"abstract":"Recent studies have demonstrated that inerter‐based dampers exhibit superior performance in mitigating cable vibration over conventional passive viscous dampers (VDs). This paper develops a new inerter‐based damper called the eddy‐current inertial mass damper (ECIMD), which consists of a rotary eddy‐current damping element and a paralleled ball screw inertial mass element. Inspired by the advantages of two VDs on a single stay cable, the damping of a stay cable with two ECIMDs, either at opposite cable ends or the same cable end, was investigated through theoretical analysis, experimental study, and parameter optimization. First, the mechanical model of the ECIMD was derived from the geometrical configuration, and its effectiveness was verified through mechanical performance tests on two ECIMD prototypes. Subsequently, theoretical analysis models of the cable‐ECIMD system were established by considering the cable sag, flexural stiffness, and boundary conditions. Furthermore, control performances of a model cable attached with two ECIMDs were experimentally evaluated. Finally, the multimode damping effect of two ECIMDs at the same cable end was highlighted through parameter optimization. Results show that when two ECIMDs are installed at opposite cable ends, the coupled single‐mode damping effect of two ECIMDs is approximately the sum of individual contributions from each ECIMD. When mechanical properties of two ECIMDs at the same cable end can match well with each other, the coupled single‐mode and multimode damping effect of two ECIMDs can be significantly enhanced compared with that of a single ECIMD installed at a further distance away from the cable anchorage.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89529893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Stress analysis is an important part of the health monitoring and evaluation of a high arch dam. At present, a reasonable quantitative analysis method for the importance of stress influencing factors of a high arch dam during the operation period remains lacking. According to measured data of strain gauge groups, a quantitative analysis method is proposed integrating succession projection algorithm (SPA), orthogonal signal correction (OSC), and partial least squares (PLS). First, based on the stress calculation of the strain gauge group of a concrete dam, the statistical model of high arch dam stress is established. Second, independent variables are preprocessed using SPA and OSC to screen out effective influencing factors without noise signals. Finally, the principal component with the strongest explanation for the dependent variable is extracted using PLS, and the importance of stress influencing factors of a high arch dam during the operation period is quantitatively separated. Results show that the SPA–OSC–PLS method can effectively eliminate the effects of multiple correlations, information overlap, and noise among influencing factors. In addition, the predictive ability and interpretability of the SPA–OSC–PLS method are superior to the PLS and SPA–PLS methods, which can reasonably obtain the importance of stress influencing factors of a high arch dam. The proposed method can accurately reveal the change law and action mechanism of the stress of a high arch dam during the operation period.
{"title":"Quantitative analysis method for the importance of stress influencing factors of a high arch dam during the operation period using SPA–OSC–PLS","authors":"Bo Li, Xiao Han, M. Yao, Jing Tian, Qian Zheng","doi":"10.1002/stc.3087","DOIUrl":"https://doi.org/10.1002/stc.3087","url":null,"abstract":"Stress analysis is an important part of the health monitoring and evaluation of a high arch dam. At present, a reasonable quantitative analysis method for the importance of stress influencing factors of a high arch dam during the operation period remains lacking. According to measured data of strain gauge groups, a quantitative analysis method is proposed integrating succession projection algorithm (SPA), orthogonal signal correction (OSC), and partial least squares (PLS). First, based on the stress calculation of the strain gauge group of a concrete dam, the statistical model of high arch dam stress is established. Second, independent variables are preprocessed using SPA and OSC to screen out effective influencing factors without noise signals. Finally, the principal component with the strongest explanation for the dependent variable is extracted using PLS, and the importance of stress influencing factors of a high arch dam during the operation period is quantitatively separated. Results show that the SPA–OSC–PLS method can effectively eliminate the effects of multiple correlations, information overlap, and noise among influencing factors. In addition, the predictive ability and interpretability of the SPA–OSC–PLS method are superior to the PLS and SPA–PLS methods, which can reasonably obtain the importance of stress influencing factors of a high arch dam. The proposed method can accurately reveal the change law and action mechanism of the stress of a high arch dam during the operation period.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"21 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89802107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The performance and optimal design of the base‐isolated structure supplemented with clutching inerter damper (CID) subjected to seismic loading are investigated. Because of the nonlinear force‐deformation behavior of the CID, the stochastic response of the isolated structure subjected to nonstationary earthquake excitation is obtained using the time‐dependent equivalent linearization technique. To investigate the effects of nonstationary earthquake characteristics, the isolated structure's nonstationary response is compared to the corresponding stationary response. For a given isolated structural system and excitation, there exists an optimum value of the CID inertance at which the root mean square absolute acceleration of the superstructure achieves a minimum value. The effects of key parameters like superstructure flexibility, isolation period, and isolation damping ratio on the CID's optimal inertance are examined. The seismic response of base‐isolated structures is also obtained under real earthquakes using the nonlinear model of the CID. The effects of the CID on the response of isolated structures under real earthquakes were found to be well correlated with those of stochastic analysis. Finally, for the approximate response and initial design of base‐isolated structures, a closed‐form expression for the equivalent damping of the CID is proposed. Using the equivalent inertance and damping of the CID, the bearing displacements and forces of isolated structures with the CID were found to be matching with that obtained by the nonlinear analysis. However, there can be an error in the prediction of structural acceleration and force in the CID by using this equivalent approach.
{"title":"Performance and optimal design of base‐isolated structures with clutching inerter damper","authors":"R. S. Jangid","doi":"10.1002/stc.3000","DOIUrl":"https://doi.org/10.1002/stc.3000","url":null,"abstract":"The performance and optimal design of the base‐isolated structure supplemented with clutching inerter damper (CID) subjected to seismic loading are investigated. Because of the nonlinear force‐deformation behavior of the CID, the stochastic response of the isolated structure subjected to nonstationary earthquake excitation is obtained using the time‐dependent equivalent linearization technique. To investigate the effects of nonstationary earthquake characteristics, the isolated structure's nonstationary response is compared to the corresponding stationary response. For a given isolated structural system and excitation, there exists an optimum value of the CID inertance at which the root mean square absolute acceleration of the superstructure achieves a minimum value. The effects of key parameters like superstructure flexibility, isolation period, and isolation damping ratio on the CID's optimal inertance are examined. The seismic response of base‐isolated structures is also obtained under real earthquakes using the nonlinear model of the CID. The effects of the CID on the response of isolated structures under real earthquakes were found to be well correlated with those of stochastic analysis. Finally, for the approximate response and initial design of base‐isolated structures, a closed‐form expression for the equivalent damping of the CID is proposed. Using the equivalent inertance and damping of the CID, the bearing displacements and forces of isolated structures with the CID were found to be matching with that obtained by the nonlinear analysis. However, there can be an error in the prediction of structural acceleration and force in the CID by using this equivalent approach.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"432 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83720437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The effect of axial loads on the dynamic interaction of a shear frame and tuned mass dampers (TMDs) is evaluated under harmonic and seismic lateral loads. Taking into account the nonlinear geometric stiffness created by the small and large TMD gravity load on the frame columns, the nonlinear differential equations of motion of coupled TMD and frame are derived. Then, the interaction between the small and large TMD and the frame is studied, and the equations of motion are investigated. Nonlinear P‐delta effects couple the TMD and frame responses. By using the method of multiple scales, the asymptotic solution of the nonlinear differential equations is derived, and the effect of two‐to‐one internal resonance, called proportional resonance, is examined. System stability under near‐internal resonance is investigated by plotting the modal amplitude responses vs. variations of excitation frequency and amplitude. The jump and saturation phenomena can be observed in the plots. A parametric study is conducted on the effect of variations of the quantities, e.g., damping ratios of the structure and TMD, the mass ratio, and the axial load ratio, on the response amplitude of the structure and TMD. The time and frequency responses of two linear and nonlinear dynamics for the TMD–structure interaction under harmonic and seismic excitation are also studied and compared.
{"title":"Nonlinear dynamic P‐delta interaction between TMD and the frame structure under proportional internal resonances","authors":"D. Afshar, M. Amin Afshar","doi":"10.1002/stc.3082","DOIUrl":"https://doi.org/10.1002/stc.3082","url":null,"abstract":"The effect of axial loads on the dynamic interaction of a shear frame and tuned mass dampers (TMDs) is evaluated under harmonic and seismic lateral loads. Taking into account the nonlinear geometric stiffness created by the small and large TMD gravity load on the frame columns, the nonlinear differential equations of motion of coupled TMD and frame are derived. Then, the interaction between the small and large TMD and the frame is studied, and the equations of motion are investigated. Nonlinear P‐delta effects couple the TMD and frame responses. By using the method of multiple scales, the asymptotic solution of the nonlinear differential equations is derived, and the effect of two‐to‐one internal resonance, called proportional resonance, is examined. System stability under near‐internal resonance is investigated by plotting the modal amplitude responses vs. variations of excitation frequency and amplitude. The jump and saturation phenomena can be observed in the plots. A parametric study is conducted on the effect of variations of the quantities, e.g., damping ratios of the structure and TMD, the mass ratio, and the axial load ratio, on the response amplitude of the structure and TMD. The time and frequency responses of two linear and nonlinear dynamics for the TMD–structure interaction under harmonic and seismic excitation are also studied and compared.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"98 2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90987913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, a sensor network configuration optimization approach is proposed to design informative and energy‐efficient wireless sensor networks. In particular, the design of cluster‐based versatile wireless sensor networks for structural health monitoring is considered. In contrast to conventional cluster‐based wireless sensor placement methods, a clustering optimization algorithm is proposed to determine the optimal locations of the cluster heads and the base station to enhance the energy efficiency of the network. The proposed approach determines the optimal wireless sensor network configuration that achieves the required estimation accuracy with minimal energy cost. Moreover, the proposed approach utilizes a holistic measure to assess the overall performance of multitype sensing devices. Furthermore, by implementing a genetic algorithm (GA) strategy, the proposed approach is computationally efficient and widely applicable for large‐scale civil engineering infrastructures. To demonstrate the performance of the proposed approach, the wireless sensor network configuration design of a bridge model and a space truss model is presented.
{"title":"Energy‐aware versatile wireless sensor network configuration for structural health monitoring","authors":"Xiaogang Hao, K. Yuen, Sin‐Chi Kuok","doi":"10.1002/stc.3083","DOIUrl":"https://doi.org/10.1002/stc.3083","url":null,"abstract":"In this paper, a sensor network configuration optimization approach is proposed to design informative and energy‐efficient wireless sensor networks. In particular, the design of cluster‐based versatile wireless sensor networks for structural health monitoring is considered. In contrast to conventional cluster‐based wireless sensor placement methods, a clustering optimization algorithm is proposed to determine the optimal locations of the cluster heads and the base station to enhance the energy efficiency of the network. The proposed approach determines the optimal wireless sensor network configuration that achieves the required estimation accuracy with minimal energy cost. Moreover, the proposed approach utilizes a holistic measure to assess the overall performance of multitype sensing devices. Furthermore, by implementing a genetic algorithm (GA) strategy, the proposed approach is computationally efficient and widely applicable for large‐scale civil engineering infrastructures. To demonstrate the performance of the proposed approach, the wireless sensor network configuration design of a bridge model and a space truss model is presented.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75170871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As inherent characteristics of bridge structures, influence lines have been successfully applied in the fields of model updating, damage detection, and condition evaluation. The fast and accurate identification of a bridge influence line (BIL) is the premise and foundation of the above applications. BIL identification can be regarded as a typically ill‐posed problem for which it is usually necessary to establish a regularization model to identify the model parameters and reconstruct the BIL. In this study, a BIL identification method that can automatically determine the regularization coefficient and quantify the uncertainties of BIL identification results is proposed. To accommodate the uncertainties involved in the measurements as well as the modeling error, an interpolation function‐aided influence line model is embedded into the Bayesian framework with Gaussian prior distribution. The most probable values (MPVs) and variance of the interpolation function coefficients are derived analytically and then further used to infer the posterior probability density function of the influence line. Numerical example of a concrete continuous beam and field test for a box girder bridge show the accuracy, efficiency and qualitative evaluation of the proposed method. The results indicate that Bayesian regularization can be used to select the optimal regularization coefficient more accurately and effectively than traditional methods. More importantly, the uncertainty quantification for the influence line can qualitatively reflect the accuracy of the results as well as the effects of the parameters of the BIL identification model.
{"title":"A statistical influence line identification method using Bayesian regularization and a polynomial interpolating function","authors":"Zhi-Wei Chen, Long Zhao, W. Yan, K. Yuen, Chen Wu","doi":"10.1002/stc.3080","DOIUrl":"https://doi.org/10.1002/stc.3080","url":null,"abstract":"As inherent characteristics of bridge structures, influence lines have been successfully applied in the fields of model updating, damage detection, and condition evaluation. The fast and accurate identification of a bridge influence line (BIL) is the premise and foundation of the above applications. BIL identification can be regarded as a typically ill‐posed problem for which it is usually necessary to establish a regularization model to identify the model parameters and reconstruct the BIL. In this study, a BIL identification method that can automatically determine the regularization coefficient and quantify the uncertainties of BIL identification results is proposed. To accommodate the uncertainties involved in the measurements as well as the modeling error, an interpolation function‐aided influence line model is embedded into the Bayesian framework with Gaussian prior distribution. The most probable values (MPVs) and variance of the interpolation function coefficients are derived analytically and then further used to infer the posterior probability density function of the influence line. Numerical example of a concrete continuous beam and field test for a box girder bridge show the accuracy, efficiency and qualitative evaluation of the proposed method. The results indicate that Bayesian regularization can be used to select the optimal regularization coefficient more accurately and effectively than traditional methods. More importantly, the uncertainty quantification for the influence line can qualitatively reflect the accuracy of the results as well as the effects of the parameters of the BIL identification model.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74253805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Damage diagnosis in the structural field (mechanical, civil, aerospace, etc.) is a topic of active development and research. In recent years, considerable enhancements in this field have been achieved mainly due to advances in sensor technologies, the evolution of signal processing algorithms, and the increase of computational power. As one of the main consequences, the amount of data recorded from the sensorial equipment has steadily grown in quantity and complexity. In addition to that, these data are almost always significantly affected by many factors, which are not only related to the presence of damages but, for instance, also to the environmental and operative conditions under which the structural system is working. In order to handle these challenges, in the last few years, new deep learning models have been proposed, based on deep and heterogeneous architectures, able to deal with big data, also containing intricate diagnostic features that are difficult to be extracted. With this aim, this paper proposes a new vibration‐based structural diagnosis tool that exploits the power of convolutional neural networks (CNNs) to extract subtle damage‐related features from complex transmissibility function (TF) spectra even in presence of potentially confounding temperature variations. The diagnostic algorithm stems from the coupling of a CNN with an unsupervised anomaly detection algorithm based on autoencoders (AEs) to neutralize the effects of temperature variations and increase the damage diagnosis accuracy. The proposed approach is demonstrated with reference to a simple, but realistic, numerical case study of a structural beam subjected to temperature changes.
{"title":"Vibration‐based structural health monitoring exploiting a combination of convolutional neural networks and autoencoders for temperature effects neutralization","authors":"M. Parziale, L. Lomazzi, M. Giglio, F. Cadini","doi":"10.1002/stc.3076","DOIUrl":"https://doi.org/10.1002/stc.3076","url":null,"abstract":"Damage diagnosis in the structural field (mechanical, civil, aerospace, etc.) is a topic of active development and research. In recent years, considerable enhancements in this field have been achieved mainly due to advances in sensor technologies, the evolution of signal processing algorithms, and the increase of computational power. As one of the main consequences, the amount of data recorded from the sensorial equipment has steadily grown in quantity and complexity. In addition to that, these data are almost always significantly affected by many factors, which are not only related to the presence of damages but, for instance, also to the environmental and operative conditions under which the structural system is working. In order to handle these challenges, in the last few years, new deep learning models have been proposed, based on deep and heterogeneous architectures, able to deal with big data, also containing intricate diagnostic features that are difficult to be extracted. With this aim, this paper proposes a new vibration‐based structural diagnosis tool that exploits the power of convolutional neural networks (CNNs) to extract subtle damage‐related features from complex transmissibility function (TF) spectra even in presence of potentially confounding temperature variations. The diagnostic algorithm stems from the coupling of a CNN with an unsupervised anomaly detection algorithm based on autoencoders (AEs) to neutralize the effects of temperature variations and increase the damage diagnosis accuracy. The proposed approach is demonstrated with reference to a simple, but realistic, numerical case study of a structural beam subjected to temperature changes.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74033154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Weihua Hu, Zeng Xu, Xiao‐Han Bian, De-Hui Tang, Wei Lu, Chao Li, J. Teng, Á. Cunha
The paper mainly reports the structural dynamic behaviors of a skyscraper under operational conditions based on a wireless distributed synchronized data acquisition (WDSA) system. First, the WDSA system is developed to conveniently acquire the structural responses from a large and complex structure with the unified Global Navigation Satellite System (GNSS) time information. The phase synchronization accuracy of the WDSA method is validated by comparing the modal parameters estimated by both wired central data acquisition (WCA) and the WDSA systems. Subsequently, the dynamic properties of a skyscraper are presented by performing operational modal analysis (OMA) based on the proposed WDSA system. Finally, the WDSA‐based continuous dynamic monitoring system is further developed to capture the long‐term structural responses at different spatial positions. The structural dynamic behaviors of the skyscraper under normal wind, typhoon and earthquake conditions are reported. The structural “whiplash effect” under both normal wind and earthquake conditions are characterized by the acceleration‐based accumulated contribution factor.
{"title":"Operational modal analysis and continuous dynamic monitoring of high‐rise building based on wireless distributed synchronized data acquisition system","authors":"Weihua Hu, Zeng Xu, Xiao‐Han Bian, De-Hui Tang, Wei Lu, Chao Li, J. Teng, Á. Cunha","doi":"10.1002/stc.3063","DOIUrl":"https://doi.org/10.1002/stc.3063","url":null,"abstract":"The paper mainly reports the structural dynamic behaviors of a skyscraper under operational conditions based on a wireless distributed synchronized data acquisition (WDSA) system. First, the WDSA system is developed to conveniently acquire the structural responses from a large and complex structure with the unified Global Navigation Satellite System (GNSS) time information. The phase synchronization accuracy of the WDSA method is validated by comparing the modal parameters estimated by both wired central data acquisition (WCA) and the WDSA systems. Subsequently, the dynamic properties of a skyscraper are presented by performing operational modal analysis (OMA) based on the proposed WDSA system. Finally, the WDSA‐based continuous dynamic monitoring system is further developed to capture the long‐term structural responses at different spatial positions. The structural dynamic behaviors of the skyscraper under normal wind, typhoon and earthquake conditions are reported. The structural “whiplash effect” under both normal wind and earthquake conditions are characterized by the acceleration‐based accumulated contribution factor.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78689252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Effect of passive vibration isolation heavily depends on force–displacement characteristic of the isolation system. In view of this dependence, this paper investigates the influence of negative stiffness device (NSD) on the effect of vibration isolation system. Detailed evaluation of transmissibility is performed. The critical parameters are identified. It is found that with NSD, significant vibration reduction for both absolute and relative displacement transmissibility is obtained. A modified Lindstedt–Poincaré method (modified L–P method) is used to obtain analytical periodic solutions for the approximated piecewise linear dynamic system. The analytical limit cycles by the modified L–P solution agree satisfactorily with the ones by numerical simulation. The most important finding of this study is that larger damping in a system with NSD helps in reducing transmissibility, thus increasing the efficacy of the isolation system; this is in contrast to other conventional isolation systems, wherein increased structural damping decreases the efficacy of vibration control in the frequency range of interest. It is worth noting that this finding of NSD enhancing the structural damping is consistent with earliest studies by senior author and collaborators.
{"title":"Reduction of transmissibility and increase in efficacy of vibration isolation using negative stiffness device with enhanced damping","authors":"Satish Nagarajaiah, Keguan Zou, Sudheendra Herkal","doi":"10.1002/stc.3081","DOIUrl":"https://doi.org/10.1002/stc.3081","url":null,"abstract":"Effect of passive vibration isolation heavily depends on force–displacement characteristic of the isolation system. In view of this dependence, this paper investigates the influence of negative stiffness device (NSD) on the effect of vibration isolation system. Detailed evaluation of transmissibility is performed. The critical parameters are identified. It is found that with NSD, significant vibration reduction for both absolute and relative displacement transmissibility is obtained. A modified Lindstedt–Poincaré method (modified L–P method) is used to obtain analytical periodic solutions for the approximated piecewise linear dynamic system. The analytical limit cycles by the modified L–P solution agree satisfactorily with the ones by numerical simulation. The most important finding of this study is that larger damping in a system with NSD helps in reducing transmissibility, thus increasing the efficacy of the isolation system; this is in contrast to other conventional isolation systems, wherein increased structural damping decreases the efficacy of vibration control in the frequency range of interest. It is worth noting that this finding of NSD enhancing the structural damping is consistent with earliest studies by senior author and collaborators.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"57 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86514737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A large amount of the world's existing infrastructure is reaching the end of its service life, requiring intervention in the form of structural rehabilitation or replacement. A critical aspect of such asset management is the condition assessment of these structures to evaluate their existing health and dictate the scheduling and extent of required rehabilitation. It has been demonstrated that human‐based manual inspections face logistical constraints and are expensive, time extensive, and subjective, depending on the knowledge of the inspection. Recently, autonomous vision‐based techniques have been proposed as an alternative, more accurate method for the inspection of deteriorating structures. Convolutional neural networks (CNNs) have demonstrated state‐of‐the‐art accuracy with respect to damage classification for concrete structures and are often implemented to process images taken from vision‐based sensors such as cameras, smartphones, and drones. However, these archetypes require a large database of annotated images to train the network to an accurate level, which is not readily available for real‐life structures. Moreover, CNNs are limited to the extent by which they are trained; they are often only trained for binary damage classification of a singular material model. This paper addresses these challenges of CNNs through the application of a generative adversarial network (GANs) for multiclass damage detection of concrete structures. The proposed GAN is trained using the SDNET2018 dataset to detect cracking, spalling, pitting, and construction joints in concrete surfaces. Moreover, transfer learning is implemented to transfer the learned features of the GAN to a CNN architecture to allow for accurate image classification. It is concluded that, for a 0%–30% reduction in the amount of labeled data used, the proposed GAN method has comparable accuracy to traditional CNNs.
{"title":"Multiclass damage detection in concrete structures using a transfer learning‐based generative adversarial networks","authors":"Kyle Dunphy, A. Sadhu, Jinfei Wang","doi":"10.1002/stc.3079","DOIUrl":"https://doi.org/10.1002/stc.3079","url":null,"abstract":"A large amount of the world's existing infrastructure is reaching the end of its service life, requiring intervention in the form of structural rehabilitation or replacement. A critical aspect of such asset management is the condition assessment of these structures to evaluate their existing health and dictate the scheduling and extent of required rehabilitation. It has been demonstrated that human‐based manual inspections face logistical constraints and are expensive, time extensive, and subjective, depending on the knowledge of the inspection. Recently, autonomous vision‐based techniques have been proposed as an alternative, more accurate method for the inspection of deteriorating structures. Convolutional neural networks (CNNs) have demonstrated state‐of‐the‐art accuracy with respect to damage classification for concrete structures and are often implemented to process images taken from vision‐based sensors such as cameras, smartphones, and drones. However, these archetypes require a large database of annotated images to train the network to an accurate level, which is not readily available for real‐life structures. Moreover, CNNs are limited to the extent by which they are trained; they are often only trained for binary damage classification of a singular material model. This paper addresses these challenges of CNNs through the application of a generative adversarial network (GANs) for multiclass damage detection of concrete structures. The proposed GAN is trained using the SDNET2018 dataset to detect cracking, spalling, pitting, and construction joints in concrete surfaces. Moreover, transfer learning is implemented to transfer the learned features of the GAN to a CNN architecture to allow for accurate image classification. It is concluded that, for a 0%–30% reduction in the amount of labeled data used, the proposed GAN method has comparable accuracy to traditional CNNs.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"74 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80172334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：