This paper presents a wavelet‐based strategy for fore‐aft vibration control of onshore horizontal axis wind turbine tower. For this purpose, an active tuned mass damper is combined with an aero‐servo‐elastic turbine model in the multi‐body framework. The combined system is exposed to turbulent wind and seismic ground motion to investigate the controller performance in extreme operating conditions. The optimal tuning is achieved by frequency‐dependent gain scheduling via wavelet transform. Analytic Morse wavelet is used as a basis function for transforming the input and feedback to recast the classical linear quadratic regulator (LQR) in the time‐frequency domain over a finite time horizon. The scale‐dependent differential Riccati equations are solved for optimal gains, which are used to estimate the optimal control force. Numerical studies presented in this paper demonstrate the advantage of the proposed gain scheduling over classical LQR. The efficiency of the proposed algorithm is verified using different flow conditions and seismic input, where the performance is compared with benchmark results.
{"title":"Wavelet linear quadratic regulator‐based gain scheduling for optimal fore‐aft vibration control of horizontal axis wind turbine tower using active tuned mass damper","authors":"Arka Mitra, Yamini Giridharan, A. Chakraborty","doi":"10.1002/stc.3055","DOIUrl":"https://doi.org/10.1002/stc.3055","url":null,"abstract":"This paper presents a wavelet‐based strategy for fore‐aft vibration control of onshore horizontal axis wind turbine tower. For this purpose, an active tuned mass damper is combined with an aero‐servo‐elastic turbine model in the multi‐body framework. The combined system is exposed to turbulent wind and seismic ground motion to investigate the controller performance in extreme operating conditions. The optimal tuning is achieved by frequency‐dependent gain scheduling via wavelet transform. Analytic Morse wavelet is used as a basis function for transforming the input and feedback to recast the classical linear quadratic regulator (LQR) in the time‐frequency domain over a finite time horizon. The scale‐dependent differential Riccati equations are solved for optimal gains, which are used to estimate the optimal control force. Numerical studies presented in this paper demonstrate the advantage of the proposed gain scheduling over classical LQR. The efficiency of the proposed algorithm is verified using different flow conditions and seismic input, where the performance is compared with benchmark results.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82210576","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}
S. Farid Ghahari, K. Sargsyan, M. Çelebi, E. Taciroglu
The use of simple models for response prediction of building structures is preferred in earthquake engineering for risk evaluations at regional scales, as they make computational studies more feasible. The primary impediment in their gainful use presently is the lack of viable methods for quantifying (and reducing upon) the modeling errors/uncertainties they bear. This study presents a Bayesian calibration method wherein the modeling error is embedded into the parameters of the model. The method is specifically described for coupled shear‐flexural beam models here, but it can be applied to any parametric surrogate model. The major benefit the method offers is the ability to consider the modeling uncertainty in the forward prediction of any degree‐of‐freedom or composite response regardless of the data used in calibration. The method is extensively verified using two synthetic examples. In the first example, the beam model is calibrated to represent a similar beam model but with enforced modeling errors. In the second example, the beam model is used to represent the detailed finite element model of a 52‐story building. Both examples show the capability of the proposed solution to provide realistic uncertainty estimation around the mean prediction.
{"title":"Quantifying modeling uncertainty in simplified beam models for building response prediction","authors":"S. Farid Ghahari, K. Sargsyan, M. Çelebi, E. Taciroglu","doi":"10.1002/stc.3078","DOIUrl":"https://doi.org/10.1002/stc.3078","url":null,"abstract":"The use of simple models for response prediction of building structures is preferred in earthquake engineering for risk evaluations at regional scales, as they make computational studies more feasible. The primary impediment in their gainful use presently is the lack of viable methods for quantifying (and reducing upon) the modeling errors/uncertainties they bear. This study presents a Bayesian calibration method wherein the modeling error is embedded into the parameters of the model. The method is specifically described for coupled shear‐flexural beam models here, but it can be applied to any parametric surrogate model. The major benefit the method offers is the ability to consider the modeling uncertainty in the forward prediction of any degree‐of‐freedom or composite response regardless of the data used in calibration. The method is extensively verified using two synthetic examples. In the first example, the beam model is calibrated to represent a similar beam model but with enforced modeling errors. In the second example, the beam model is used to represent the detailed finite element model of a 52‐story building. Both examples show the capability of the proposed solution to provide realistic uncertainty estimation around the mean prediction.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"69 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79929840","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}
Currently, structural health monitoring (SHM) of complex metallic structures based on the localization and identification of acoustic emission (AE) sources has become one of the most common condition monitoring method. However, existing methods are difficulty in accurately localizing and identifying AE sources generated by complex metallic structures that have been surface modified or machined. To overcome this problem, this paper presents a novel architecture named nearfield frequency space sparse decomposition (NFSSD) for localizing AE sources collected from complex metallic structures. Main contributions of the proposed NFSSD are to incorporate the decomposed subbands of AE signal in frequency into the traditional sparse decomposition (SD), which can extract more effective information and improve the identification of coherent AE sources. On this basis, NFSSD‐based AE feature extraction scheme is further proposed for improving the accuracy and stability of AE source localization for complex metallic structures. First, all frequency point estimates of the original AE signal used to divide the subbands are obtained, where each frequency corresponds to the center frequency of the subband. Furthermore, the spatial spectrum of each subband signal is solved over the entire spatial domain, and the spatial spectrum of the signal is obtained to estimate the location of AE source. Two experimental results of coordinate‐based AE source localization of complex metallic structures indicate that the proposed method has better AE source localization performance compared to conventional localization approaches. Specifically, the results show that the proposed approach can provide an effective theoretical reference for AE‐based SHM of complex metallic structures.
{"title":"Acoustic emission sources localization and identification of complex metallic structures based on nearfield frequency space sparse decomposition","authors":"Yang Li, Chi-Guhn Lee, Feiyun Xu","doi":"10.1002/stc.3064","DOIUrl":"https://doi.org/10.1002/stc.3064","url":null,"abstract":"Currently, structural health monitoring (SHM) of complex metallic structures based on the localization and identification of acoustic emission (AE) sources has become one of the most common condition monitoring method. However, existing methods are difficulty in accurately localizing and identifying AE sources generated by complex metallic structures that have been surface modified or machined. To overcome this problem, this paper presents a novel architecture named nearfield frequency space sparse decomposition (NFSSD) for localizing AE sources collected from complex metallic structures. Main contributions of the proposed NFSSD are to incorporate the decomposed subbands of AE signal in frequency into the traditional sparse decomposition (SD), which can extract more effective information and improve the identification of coherent AE sources. On this basis, NFSSD‐based AE feature extraction scheme is further proposed for improving the accuracy and stability of AE source localization for complex metallic structures. First, all frequency point estimates of the original AE signal used to divide the subbands are obtained, where each frequency corresponds to the center frequency of the subband. Furthermore, the spatial spectrum of each subband signal is solved over the entire spatial domain, and the spatial spectrum of the signal is obtained to estimate the location of AE source. Two experimental results of coordinate‐based AE source localization of complex metallic structures indicate that the proposed method has better AE source localization performance compared to conventional localization approaches. Specifically, the results show that the proposed approach can provide an effective theoretical reference for AE‐based SHM of complex metallic structures.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"98 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80810539","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}
Qi‐Ang Wang, Cheng Zhang, Zhan-guo Ma, Guiyue Jiao, Xiao‐Wei Jiang, Y. Ni, Ying‐Chao Wang, Yu‐Tong Du, Gao‐Bo Qu, Jiandong Huang
Engineering structures are subjected to strain and deflection, due to various loads, and/or environmental effects. It is, thus, of uttermost importance to monitor the strain condition of critical structures, so as to prevent catastrophic failures, but also to minimize maintenance costs. In order to overcome limitations of existing conventional strain sensors, including extensive cabling arrangement and continuous power supply, a newly dual‐interrogation‐mode radio frequency identification (RFID) strain sensor is proposed in this study to achieve a longer interrogation transmission distance for wireless strain sensing, which can automatically switch between passive modes with low power consumption and active modes with ultra‐high frequency (UHF). The proposed design scheme involves the RFID tag and RFID reader for wireless strain transmission module and the improved Wheatstone bridge as strain measurement module. The proposed RFID strain sensor features the following merits: (i) Wireless strain sensing characteristics with the integration of RFID technology. (ii) Long transmission distance with dual interrogation mode: RFID tag is generally in a passive dormant state with an extremely low operating current. And the tag circuit will enter the working state in ultra‐high frequency to collect strain data only when the RFID reader enters the interrogation area, achieving semi‐active strain sensing with low energy consumption at a long distance (up to 80 m), which is especially suitable for practical strain measurement of engineering structures. (iii) Temperature self‐compensation characteristic: The developed RFID sensor includes a temperature compensation strain gauge to offset the error caused by temperature change, which will improve the measurement accuracy. Finally, extensive experiments are conducted to characterize the measurement performance, including thermal stability, tensile, and compressive strain sensing for various engineering materials.
{"title":"Towards long‐transmission‐distance and semi‐active wireless strain sensing enabled by dual‐interrogation‐mode RFID technology","authors":"Qi‐Ang Wang, Cheng Zhang, Zhan-guo Ma, Guiyue Jiao, Xiao‐Wei Jiang, Y. Ni, Ying‐Chao Wang, Yu‐Tong Du, Gao‐Bo Qu, Jiandong Huang","doi":"10.1002/stc.3069","DOIUrl":"https://doi.org/10.1002/stc.3069","url":null,"abstract":"Engineering structures are subjected to strain and deflection, due to various loads, and/or environmental effects. It is, thus, of uttermost importance to monitor the strain condition of critical structures, so as to prevent catastrophic failures, but also to minimize maintenance costs. In order to overcome limitations of existing conventional strain sensors, including extensive cabling arrangement and continuous power supply, a newly dual‐interrogation‐mode radio frequency identification (RFID) strain sensor is proposed in this study to achieve a longer interrogation transmission distance for wireless strain sensing, which can automatically switch between passive modes with low power consumption and active modes with ultra‐high frequency (UHF). The proposed design scheme involves the RFID tag and RFID reader for wireless strain transmission module and the improved Wheatstone bridge as strain measurement module. The proposed RFID strain sensor features the following merits: (i) Wireless strain sensing characteristics with the integration of RFID technology. (ii) Long transmission distance with dual interrogation mode: RFID tag is generally in a passive dormant state with an extremely low operating current. And the tag circuit will enter the working state in ultra‐high frequency to collect strain data only when the RFID reader enters the interrogation area, achieving semi‐active strain sensing with low energy consumption at a long distance (up to 80 m), which is especially suitable for practical strain measurement of engineering structures. (iii) Temperature self‐compensation characteristic: The developed RFID sensor includes a temperature compensation strain gauge to offset the error caused by temperature change, which will improve the measurement accuracy. Finally, extensive experiments are conducted to characterize the measurement performance, including thermal stability, tensile, and compressive strain sensing for various engineering materials.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85194860","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}
Rouzbeh Doroudi, Seyed Hossein Hosseini Lavassani, M. Shahrouzi, M. Dadgostar
In this study, multivariate empirical mode decomposition (MEMD) is used to evaluate the dynamic characteristics of super‐tall buildings. Two super‐tall buildings, including Milad Tower, which is located in Tehran, Iran, and Canton Tower, which is located in Guangzhou, China, are used as examples to estimate the capability of multivariate empirical mode decomposition for recognizing the dynamic characteristics of buildings. A method is suggested to extract the frequency of structures automatically. First, the best segment of required data, including acceleration response and wind speed is found, and then wavelet transform is used to eliminate the noise and find proper and wanted natural frequency. Finally, to investigate all signals, that is, acceleration responses of all channels simultaneously, MEMD is applied to identify the frequency of the filtered signals. The extracted frequencies are selected in the order of amplitude power of each mode for each intrinsic mode function (IMF). The obtained results are appropriate, corresponding to other studies. Hence, the proposed method can automatically select the accurate frequency of super‐tall buildings in less time duration by considering all required data simultaneously.
{"title":"Identifying the dynamic characteristics of super tall buildings by multivariate empirical mode decomposition","authors":"Rouzbeh Doroudi, Seyed Hossein Hosseini Lavassani, M. Shahrouzi, M. Dadgostar","doi":"10.1002/stc.3075","DOIUrl":"https://doi.org/10.1002/stc.3075","url":null,"abstract":"In this study, multivariate empirical mode decomposition (MEMD) is used to evaluate the dynamic characteristics of super‐tall buildings. Two super‐tall buildings, including Milad Tower, which is located in Tehran, Iran, and Canton Tower, which is located in Guangzhou, China, are used as examples to estimate the capability of multivariate empirical mode decomposition for recognizing the dynamic characteristics of buildings. A method is suggested to extract the frequency of structures automatically. First, the best segment of required data, including acceleration response and wind speed is found, and then wavelet transform is used to eliminate the noise and find proper and wanted natural frequency. Finally, to investigate all signals, that is, acceleration responses of all channels simultaneously, MEMD is applied to identify the frequency of the filtered signals. The extracted frequencies are selected in the order of amplitude power of each mode for each intrinsic mode function (IMF). The obtained results are appropriate, corresponding to other studies. Hence, the proposed method can automatically select the accurate frequency of super‐tall buildings in less time duration by considering all required data simultaneously.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"19 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79167613","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}
This paper provides a novel and effective self‐adaptive real‐time clustering (SARTC) strategy for clustering real‐world large datasets real time, and a novel feature selection method (LS‐MI) was proposed to enhance the clustering efficiency. The effectiveness of the novel methods was validated by theoretical analysis and experimental verification on three benchmark datasets; the result shows that the novel methods achieved the superiorities of high efficiency, high accuracy, and adaptive convergence. And the novel methods were applied to damage pattern recognition for steel tube confined reinforced concrete columns through acoustic emission (AE) signals; the result shows that the proposed LS‐MI procedure can retain AE features with strong representativity but low redundancy, while the SARTC strategy can classify the real‐time AE signals into three clusters with clear bonds. The generalized AE clustering structure was discussed, and possible relation of the clusters to the damage types were explicated; these results create a foundation for establishment of general AE interpretation rules for damage mode identification in future works.
{"title":"Self‐adaptive real‐time clustering analysis and damage pattern recognition for steel tube confined reinforced concrete structures through acoustic emission signals","authors":"Fangzhu Du, Xiuling Li, Dongsheng Li, Wei Shen","doi":"10.1002/stc.3071","DOIUrl":"https://doi.org/10.1002/stc.3071","url":null,"abstract":"This paper provides a novel and effective self‐adaptive real‐time clustering (SARTC) strategy for clustering real‐world large datasets real time, and a novel feature selection method (LS‐MI) was proposed to enhance the clustering efficiency. The effectiveness of the novel methods was validated by theoretical analysis and experimental verification on three benchmark datasets; the result shows that the novel methods achieved the superiorities of high efficiency, high accuracy, and adaptive convergence. And the novel methods were applied to damage pattern recognition for steel tube confined reinforced concrete columns through acoustic emission (AE) signals; the result shows that the proposed LS‐MI procedure can retain AE features with strong representativity but low redundancy, while the SARTC strategy can classify the real‐time AE signals into three clusters with clear bonds. The generalized AE clustering structure was discussed, and possible relation of the clusters to the damage types were explicated; these results create a foundation for establishment of general AE interpretation rules for damage mode identification in future works.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84430119","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}
Stefan Wernitz, Benedikt Hofmeister, Clemens Jonscher, T. Griessmann, R. Rolfes
Vibration‐based Structural Health Monitoring is an ongoing field of research in many engineering disciplines. As for civil engineering, plenty of experimental structures have been erected in the past decades, both under laboratory and real‐life conditions. Some of these facilities became a benchmark for different kinds of methods associated with Structural Health Monitoring such as damage analysis and Operational Modal Analysis, which led to fruitful developments in the global research community. When it comes to the continuous monitoring and assessment of the structural integrity of mechanical systems exposed to environmental and operational variability, the robustness and adaptability of the applied methods is of utmost importance. Such properties cannot be fully evaluated under laboratory conditions, which highlights the necessity of outdoor measurement campaigns. To this end, we introduce a test facility for Structural Health Monitoring comprising a lattice tower exposed to realistic conditions and featuring multiple reversible damage mechanisms. The structure located near Hanover in Northern Germany is densely equipped with sensors to capture the structural dynamics. The environmental conditions are monitored in parallel. The obtained continuous measurement data can be accessed online in an open repository. That is the foundation for benchmarks, consisting of a growing data set that enables the development, evaluation, and comparison of Structural Health Monitoring strategies and methods. In this article, we offer a documentation of the test facility and the data acquisition system. Lastly, we characterize the structural dynamics with the help of a finite element model and by analyzing several month of data.
{"title":"A new open‐database benchmark structure for vibration‐based Structural Health Monitoring","authors":"Stefan Wernitz, Benedikt Hofmeister, Clemens Jonscher, T. Griessmann, R. Rolfes","doi":"10.1002/stc.3077","DOIUrl":"https://doi.org/10.1002/stc.3077","url":null,"abstract":"Vibration‐based Structural Health Monitoring is an ongoing field of research in many engineering disciplines. As for civil engineering, plenty of experimental structures have been erected in the past decades, both under laboratory and real‐life conditions. Some of these facilities became a benchmark for different kinds of methods associated with Structural Health Monitoring such as damage analysis and Operational Modal Analysis, which led to fruitful developments in the global research community. When it comes to the continuous monitoring and assessment of the structural integrity of mechanical systems exposed to environmental and operational variability, the robustness and adaptability of the applied methods is of utmost importance. Such properties cannot be fully evaluated under laboratory conditions, which highlights the necessity of outdoor measurement campaigns. To this end, we introduce a test facility for Structural Health Monitoring comprising a lattice tower exposed to realistic conditions and featuring multiple reversible damage mechanisms. The structure located near Hanover in Northern Germany is densely equipped with sensors to capture the structural dynamics. The environmental conditions are monitored in parallel. The obtained continuous measurement data can be accessed online in an open repository. That is the foundation for benchmarks, consisting of a growing data set that enables the development, evaluation, and comparison of Structural Health Monitoring strategies and methods. In this article, we offer a documentation of the test facility and the data acquisition system. Lastly, we characterize the structural dynamics with the help of a finite element model and by analyzing several month of data.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"29 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89943987","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 proportion of groundwater‐related diseases in the operational high‐speed railway tunnels in China is increasing and rapid and accurate disease monitoring is urgently needed. Therefore, it is a new attempt to monitor 5‐ to 10‐m water‐bearing anomalies in operating tunnel structures by using train‐borne transient electromagnetic method. The stationary interference source train tracks in the tunnel environment have serious electromagnetic interference to the monitoring of water‐bearing anomalies. Thus, this paper combines numerical simulations and indoor experiments to carry out research on the minimum water‐bearing anomalies that can be monitored at such close distances by train‐borne transient electromagnetic method under electromagnetic interference from train tracks. First, a comparative study of the electromagnetic characteristics of the water‐bearing anomalies when their own parameters change is carried out by numerical simulation, followed by a comparative analysis of the electromagnetic response of the water‐bearing anomalies under the interference of train tracks. For the missing electromagnetic response of the coil‐metal‐anomaly in the numerical simulation, a full‐scale physical model experiment is conducted to obtain the time range of the three interferences. Also in the experiments, the feasibility of existing instruments for close range water‐bearing anomalies detection is verified by comparing different transient electromagnetic instruments. Finally, the minimum water‐bearing anomalies that can be monitored in close proximity under the interference of train tracks are obtained experimentally.
{"title":"Study on detection range of short distance water‐bearing anomaly via train‐borne transient electromagnetic method under interference of train tracks","authors":"Zongyang Li, Taiyue Qi","doi":"10.1002/stc.3059","DOIUrl":"https://doi.org/10.1002/stc.3059","url":null,"abstract":"The proportion of groundwater‐related diseases in the operational high‐speed railway tunnels in China is increasing and rapid and accurate disease monitoring is urgently needed. Therefore, it is a new attempt to monitor 5‐ to 10‐m water‐bearing anomalies in operating tunnel structures by using train‐borne transient electromagnetic method. The stationary interference source train tracks in the tunnel environment have serious electromagnetic interference to the monitoring of water‐bearing anomalies. Thus, this paper combines numerical simulations and indoor experiments to carry out research on the minimum water‐bearing anomalies that can be monitored at such close distances by train‐borne transient electromagnetic method under electromagnetic interference from train tracks. First, a comparative study of the electromagnetic characteristics of the water‐bearing anomalies when their own parameters change is carried out by numerical simulation, followed by a comparative analysis of the electromagnetic response of the water‐bearing anomalies under the interference of train tracks. For the missing electromagnetic response of the coil‐metal‐anomaly in the numerical simulation, a full‐scale physical model experiment is conducted to obtain the time range of the three interferences. Also in the experiments, the feasibility of existing instruments for close range water‐bearing anomalies detection is verified by comparing different transient electromagnetic instruments. Finally, the minimum water‐bearing anomalies that can be monitored in close proximity under the interference of train tracks are obtained experimentally.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72829242","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}
Lanxin Luo, Ye Xia, Ao Wang, Xiaoming Lei, Xudong Jian, Limin Sun
Accurate finite element (FE) models play an essential role in the health monitoring of operational bridges. Static structural deflections caused by vehicles, which are used in traditional finite element model updating (FEMU) methods, are often procured from field tests, interrupting the traffic and limiting the test loading scenarios. This study proposes a FEMU method that directly applies the massive, multi‐source structural and traffic data in the operation phase to update the FE model, effectively solving the defects above. We use the computer vision‐based vehicle load identification technique to accurately locate and weigh vehicle loads and carry out static simulations in the FE model based on the identified vehicle loads. The proposed FEMU objective function is established using indices including dynamic structural characteristics and vehicle‐induced static structural responses. The static error index in the objective function integrates the curve shape and extrema difference of theoretic and measured static responses. Finally, we deploy a parallel particle swarm optimization (PSO) algorithm to find the global optimal updated FE model. A continuous scale bridge model is employed in the experimental studies with four typical scenarios. Compared to the results from the initial FE model, the updated FE model provides significantly better results both in dynamic and static aspects in all scenarios, and the static error indexes reduce by 75% on average. The proposed method offers a practical approach to deploying the monitoring data for real‐time FEMU, which considers dynamic and static features and provides a basis for damage detection, performance assessment, and management.
{"title":"Finite element model updating method for continuous girder bridges using monitoring responses and traffic videos","authors":"Lanxin Luo, Ye Xia, Ao Wang, Xiaoming Lei, Xudong Jian, Limin Sun","doi":"10.1002/stc.3062","DOIUrl":"https://doi.org/10.1002/stc.3062","url":null,"abstract":"Accurate finite element (FE) models play an essential role in the health monitoring of operational bridges. Static structural deflections caused by vehicles, which are used in traditional finite element model updating (FEMU) methods, are often procured from field tests, interrupting the traffic and limiting the test loading scenarios. This study proposes a FEMU method that directly applies the massive, multi‐source structural and traffic data in the operation phase to update the FE model, effectively solving the defects above. We use the computer vision‐based vehicle load identification technique to accurately locate and weigh vehicle loads and carry out static simulations in the FE model based on the identified vehicle loads. The proposed FEMU objective function is established using indices including dynamic structural characteristics and vehicle‐induced static structural responses. The static error index in the objective function integrates the curve shape and extrema difference of theoretic and measured static responses. Finally, we deploy a parallel particle swarm optimization (PSO) algorithm to find the global optimal updated FE model. A continuous scale bridge model is employed in the experimental studies with four typical scenarios. Compared to the results from the initial FE model, the updated FE model provides significantly better results both in dynamic and static aspects in all scenarios, and the static error indexes reduce by 75% on average. The proposed method offers a practical approach to deploying the monitoring data for real‐time FEMU, which considers dynamic and static features and provides a basis for damage detection, performance assessment, and management.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"91 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83773862","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 study, an active vibration mitigation of bladed structures with piezoelectric patches utilizing decentralized negative derivative feedback (NDF) controllers is evaluated numerically and experimentally. Such structures have protruding identical blades, which create numerous modes in a short interval of frequency named as high modal density or mode family. Therefore, mitigating these modes is quite challenging. As a case study, a bladed rail is considered with 5 blades, which subsequently has 5 modes in a family of mode in a very short frequency range. A numerical model of the bladed rail including 5 pairs of piezoelectric patches (sensors and actuators) is extracted. Afterwards, a decentralized NDF controller is designed based on maximum damping and H2 method for this model, which is desirable for reducing vibration corresponding to the first family mode. The numerical results show a perfect performance of the proposed controller on high modal density vibration attenuations. For validating these results, two separate bladed rails have been manufactured, and different piezoelectric patches have been attached to them. The same procedure for designing NDF controller has been done for both of the structures. Experimental results show that the family mode of the bladed rail is completely damped using decentralized NDF controller. Even though the pole‐zero patterns change from the first structure to the second one, the controller can easily mitigate the family mode vibration flawlessly. This shows high applicability of proposed controller on mitigating high modal density modes.
{"title":"High modal density active vibration attenuation of bladed structure with a decentralized optimal negative derivative feedback controller","authors":"Rasa Jamshidi, A. Paknejad, C. Collette","doi":"10.1002/stc.3056","DOIUrl":"https://doi.org/10.1002/stc.3056","url":null,"abstract":"In this study, an active vibration mitigation of bladed structures with piezoelectric patches utilizing decentralized negative derivative feedback (NDF) controllers is evaluated numerically and experimentally. Such structures have protruding identical blades, which create numerous modes in a short interval of frequency named as high modal density or mode family. Therefore, mitigating these modes is quite challenging. As a case study, a bladed rail is considered with 5 blades, which subsequently has 5 modes in a family of mode in a very short frequency range. A numerical model of the bladed rail including 5 pairs of piezoelectric patches (sensors and actuators) is extracted. Afterwards, a decentralized NDF controller is designed based on maximum damping and H2 method for this model, which is desirable for reducing vibration corresponding to the first family mode. The numerical results show a perfect performance of the proposed controller on high modal density vibration attenuations. For validating these results, two separate bladed rails have been manufactured, and different piezoelectric patches have been attached to them. The same procedure for designing NDF controller has been done for both of the structures. Experimental results show that the family mode of the bladed rail is completely damped using decentralized NDF controller. Even though the pole‐zero patterns change from the first structure to the second one, the controller can easily mitigate the family mode vibration flawlessly. This shows high applicability of proposed controller on mitigating high modal density modes.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"35 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84522772","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}
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