For the wind speed prediction, many researchers have established prediction models based on machine learning methods, statistical methods, and theoretical methods, that is, direct methods. However, the direct method cannot be widely used in the wind direction prediction because the wind direction has strong randomness and uncertainty. In order to solve this problem, this paper proposed a wind direction prediction method, that is, indirect method. Specifically, the wind speed is decomposed into crosswind speed and alongwind speed considering the correlation between wind speed and wind direction. The crosswind speed and alongwind speed are predicted based on long short-term memory (LSTM) model with empirical mode decomposition (EMD), and then, the wind direction prediction value can be calculated, that is, the wind direction prediction is realized. One-month wind monitoring data collected by the structural health monitoring (SHM) system installed on investigated bridge are employed to demonstrate the effectiveness of direct and indirect prediction for forecasting the wind speed and wind direction.
{"title":"A Multistep Direct and Indirect Strategy for Predicting Wind Direction Based on the EMD-LSTM Model","authors":"Yang Ding, X. Ye, Yong Guo","doi":"10.1155/2023/4950487","DOIUrl":"https://doi.org/10.1155/2023/4950487","url":null,"abstract":"For the wind speed prediction, many researchers have established prediction models based on machine learning methods, statistical methods, and theoretical methods, that is, direct methods. However, the direct method cannot be widely used in the wind direction prediction because the wind direction has strong randomness and uncertainty. In order to solve this problem, this paper proposed a wind direction prediction method, that is, indirect method. Specifically, the wind speed is decomposed into crosswind speed and alongwind speed considering the correlation between wind speed and wind direction. The crosswind speed and alongwind speed are predicted based on long short-term memory (LSTM) model with empirical mode decomposition (EMD), and then, the wind direction prediction value can be calculated, that is, the wind direction prediction is realized. One-month wind monitoring data collected by the structural health monitoring (SHM) system installed on investigated bridge are employed to demonstrate the effectiveness of direct and indirect prediction for forecasting the wind speed and wind direction.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84331934","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}
Xia Yang, Minghui Zhang, Hongbing Chen, Hong Hao, Qingzhao Kong
Concrete is the most commonly used construction material in infrastructural projects, but it may suffer from damages because of the heavy loads, fatigue, and harsh service environments. Therefore, it is crucial to detect damage for evaluating the structural conditions and providing guidance for daily maintenance and timely alarm. This paper presents a novel method for damage assessment that offers an easy-carried detection process with a large monitoring range. The proposed method involves exciting stress waves using a force-hammer and receiving them with piezoceramics pasted on the structure. The structural conditions are then evaluated using the Pearson correlation coefficient (PCC) of stress waves received from different stages. To verify the feasibility of the proposed method, a numerical model is innovatively established to study the stress wave propagation in a reinforced concrete (RC) beam with actual damage induced by the external load based on the concrete damaged plasticity (CDP) model. The experimental study is then conducted to demonstrate the effectiveness of the method and the accuracy of the numerical simulation. The numerical and experimental results show a good correlation, illustrating that the proposed method can not only effectively distinguish whether damage occurs but also determine the structural condition from the elastic phase to failure. The proposed monitoring method in this study has great potential for fast damage assessment of RC structures for both lab research and practical applications.
{"title":"A Novel Damage Assessment Method for RC Beam Using Force-Hammer Excitation and Piezoelectric Sensing Technology","authors":"Xia Yang, Minghui Zhang, Hongbing Chen, Hong Hao, Qingzhao Kong","doi":"10.1155/2023/4365213","DOIUrl":"https://doi.org/10.1155/2023/4365213","url":null,"abstract":"Concrete is the most commonly used construction material in infrastructural projects, but it may suffer from damages because of the heavy loads, fatigue, and harsh service environments. Therefore, it is crucial to detect damage for evaluating the structural conditions and providing guidance for daily maintenance and timely alarm. This paper presents a novel method for damage assessment that offers an easy-carried detection process with a large monitoring range. The proposed method involves exciting stress waves using a force-hammer and receiving them with piezoceramics pasted on the structure. The structural conditions are then evaluated using the Pearson correlation coefficient (PCC) of stress waves received from different stages. To verify the feasibility of the proposed method, a numerical model is innovatively established to study the stress wave propagation in a reinforced concrete (RC) beam with actual damage induced by the external load based on the concrete damaged plasticity (CDP) model. The experimental study is then conducted to demonstrate the effectiveness of the method and the accuracy of the numerical simulation. The numerical and experimental results show a good correlation, illustrating that the proposed method can not only effectively distinguish whether damage occurs but also determine the structural condition from the elastic phase to failure. The proposed monitoring method in this study has great potential for fast damage assessment of RC structures for both lab research and practical applications.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"55 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83579895","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}
Hinge joint performance during the operation of prefabricated prestressed concrete (PC) hollow slab bridges is critical to ensure their lateral collaborative working condition and safe serviceability. Traditional performance identification of hinge joints mainly relies on manual inspection, which is inefficient and inaccurate. At the same time, existing indexes (such as acceleration and strain) can only qualitatively detect the damage to hinge joints. This study proposes a novelty detection method based on impact vibration testing to rapidly perform the quantitative assessment of the working condition of the hinge joints. The relationship between hinge joint performance and lateral load distribution (LLD) is first derived in detail by theoretical analysis. And then, the quantitative analysis of collaborative performance is converted to the identification of the LLD influence line, which is innovatively established by the lateral flexibility of the hollow slab bridge. The effectiveness of the proposed method is verified through a multibeam model using ABAQUS software, and the lateral collaborative working relationship between slabs is simulated using the connector elements. Furthermore, the LLD influence lines and hinge joints performance of a PC hollow slab Yanhu Bridge are evaluated based on the impact vibration testing with sensor lateral arrangement strategy. The detection results show that the proposed method can quickly and accurately identify the damage location and the stiffness loss of hinge joints.
{"title":"Hinge Joints Performance Assessment of a PC Hollow Slab Bridge Based on Impact Vibration Testing","authors":"Q. Xia, Yi-chen Zhou, Yuyao Cheng, Jian Zhang","doi":"10.1155/2023/1834669","DOIUrl":"https://doi.org/10.1155/2023/1834669","url":null,"abstract":"Hinge joint performance during the operation of prefabricated prestressed concrete (PC) hollow slab bridges is critical to ensure their lateral collaborative working condition and safe serviceability. Traditional performance identification of hinge joints mainly relies on manual inspection, which is inefficient and inaccurate. At the same time, existing indexes (such as acceleration and strain) can only qualitatively detect the damage to hinge joints. This study proposes a novelty detection method based on impact vibration testing to rapidly perform the quantitative assessment of the working condition of the hinge joints. The relationship between hinge joint performance and lateral load distribution (LLD) is first derived in detail by theoretical analysis. And then, the quantitative analysis of collaborative performance is converted to the identification of the LLD influence line, which is innovatively established by the lateral flexibility of the hollow slab bridge. The effectiveness of the proposed method is verified through a multibeam model using ABAQUS software, and the lateral collaborative working relationship between slabs is simulated using the connector elements. Furthermore, the LLD influence lines and hinge joints performance of a PC hollow slab Yanhu Bridge are evaluated based on the impact vibration testing with sensor lateral arrangement strategy. The detection results show that the proposed method can quickly and accurately identify the damage location and the stiffness loss of hinge joints.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"142 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77820646","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}
Stagnant water in asphalt-overlaid bridge decks is a primary cause of deterioration. Rainwater seeping through the asphalt layer stagnates on waterproofing membranes of the bridge deck, consequently degrading the asphalt pavement and the underlying concrete deck. Thus, identifying ponding regions under pavements potentially containing water can facilitate the prognostic maintenance of bridge decks. This study proposes a framework to estimate the subsurface ponding zone in bridge decks using ground-penetrating radar (GPR). The depth distribution of the nonpermeable layer in the subsurface of the bridge is extracted (depth map) from the GPR C-scan using a conventional thickness evaluation method and used to build a bathymetric dendrogram to model subsurface water flows. The subsurface ponding zone can be identified by considering drainage on the bathymetric dendrogram. The proposed framework is demonstrated using an in-service bridge in Korea. The estimated subsurface ponding zone is compared with damage locations of concrete observed after hydrodemolition.
{"title":"Estimation of Water Stagnation in Asphalt-Overlaid Bridges Using Ground-Penetrating Radar","authors":"Junhwa Lee, Jinwoong Choi, Yooseong Shin, S. Sim","doi":"10.1155/2023/7280555","DOIUrl":"https://doi.org/10.1155/2023/7280555","url":null,"abstract":"Stagnant water in asphalt-overlaid bridge decks is a primary cause of deterioration. Rainwater seeping through the asphalt layer stagnates on waterproofing membranes of the bridge deck, consequently degrading the asphalt pavement and the underlying concrete deck. Thus, identifying ponding regions under pavements potentially containing water can facilitate the prognostic maintenance of bridge decks. This study proposes a framework to estimate the subsurface ponding zone in bridge decks using ground-penetrating radar (GPR). The depth distribution of the nonpermeable layer in the subsurface of the bridge is extracted (depth map) from the GPR C-scan using a conventional thickness evaluation method and used to build a bathymetric dendrogram to model subsurface water flows. The subsurface ponding zone can be identified by considering drainage on the bathymetric dendrogram. The proposed framework is demonstrated using an in-service bridge in Korea. The estimated subsurface ponding zone is compared with damage locations of concrete observed after hydrodemolition.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77413859","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}
Existing isolation methods for seismic control of underground structures show that increasing the energy dissipation effect for isolation bearings tends to unfavorably add the relative deformation and force responses of the isolated columns. Exploring high-performance energy dissipaters is necessary for simultaneously controlling multiple performance indices of isolated underground structures. In this study, an inerter-based isolation system installed in a subway station is proposed to isolate columns and dissipate input energy benefited by its mass amplification and damping enhancement mechanisms. The inerter is a two-terminal relative-acceleration-related inertial device that can adjust structural inertial properties but scarcely increase actual physical mass. A method for the development of the user-defined inerter element is proposed and used because of the absence of inerter elements in existing finite element software. Then, the soil-underground structure model is established to simulate a typical subway station with the inerter-based isolation system used at the top of the column. Parameter studies together with design cases are conducted under horizontal and vertical input excitations with different frequency components. The results show that the inerter-based system can simultaneously control multiple performance indices of the subway station, including the relative deformation, shear force, bending moment of the central column, and the horizontal relative deformation of the isolation layer. Meanwhile, the inerter-based system can realize the high-efficiency energy dissipation control effect with low demands for damping due to the damping enhancement. A large proportion of energy is first absorbed by the inerter and then reserved by the kinetic and potential energy of the inerter-based system. Therefore, the proposed inerter-based isolation system is effective for enhancing columns and reducing lateral dynamic responses, which can prevent underground structures from collapsing.
{"title":"Seismic Performance of an Underground Structure with an Inerter-Based Isolation System","authors":"Qingjun Chen, Luqi Zhang, Ruifu Zhang, Chao Pan","doi":"10.1155/2023/1349363","DOIUrl":"https://doi.org/10.1155/2023/1349363","url":null,"abstract":"Existing isolation methods for seismic control of underground structures show that increasing the energy dissipation effect for isolation bearings tends to unfavorably add the relative deformation and force responses of the isolated columns. Exploring high-performance energy dissipaters is necessary for simultaneously controlling multiple performance indices of isolated underground structures. In this study, an inerter-based isolation system installed in a subway station is proposed to isolate columns and dissipate input energy benefited by its mass amplification and damping enhancement mechanisms. The inerter is a two-terminal relative-acceleration-related inertial device that can adjust structural inertial properties but scarcely increase actual physical mass. A method for the development of the user-defined inerter element is proposed and used because of the absence of inerter elements in existing finite element software. Then, the soil-underground structure model is established to simulate a typical subway station with the inerter-based isolation system used at the top of the column. Parameter studies together with design cases are conducted under horizontal and vertical input excitations with different frequency components. The results show that the inerter-based system can simultaneously control multiple performance indices of the subway station, including the relative deformation, shear force, bending moment of the central column, and the horizontal relative deformation of the isolation layer. Meanwhile, the inerter-based system can realize the high-efficiency energy dissipation control effect with low demands for damping due to the damping enhancement. A large proportion of energy is first absorbed by the inerter and then reserved by the kinetic and potential energy of the inerter-based system. Therefore, the proposed inerter-based isolation system is effective for enhancing columns and reducing lateral dynamic responses, which can prevent underground structures from collapsing.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83300870","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}
Recently, enhancing conventional tuned mass dampers (TMDs) with a pounding damping mechanism is demonstrated to be an efficient way for vibration control of flexible structures. In this paper, a double-tuned pendulum mass damper employing a pounding damping mechanism (DTPMD-PD) is proposed. DTPMD-PD dissipates energy through the collision between distributed balls with a smaller mass and viscoelastic (VE) boundary, which can effectively reduce noise during operation compared to conventional impact dampers. Moreover, DTPMD-PD utilizes a double-tuning mechanism, and its control performance is significantly enhanced. The motion equations of a multiple degree of freedom (MDOF) structure equipped with DTPMD-PD are formulated. Based on the H∞ optimization criterion, a numerical optimization is performed to obtain the optimal design parameters of DTPMD-PD. Additionally, the pounding dissipation capacity and the parametric identification of the impact force model are investigated through free pounding experiments, and the control performance and robustness of DTPMD-PD are experimentally studied in the laboratory. The results show that the proposed numerical modeling method has considerable accuracy through experimental verifications. The restitution coefficient of the pounding layer has a significant influence on the performance of proposed DTPMD-PD. Optimized DTPMD-PD has better effectiveness than conventional TMDs under harmonic and seismic loads.
{"title":"A Double-Tuned Pendulum Mass Damper Employing a Pounding Damping Mechanism for Vibration Control of High-Rise Structures","authors":"Wenxi Wang, Tianfu Yu, Zhilin Yang, Hongyi Zhang, Xugang Hua","doi":"10.1155/2023/7686917","DOIUrl":"https://doi.org/10.1155/2023/7686917","url":null,"abstract":"Recently, enhancing conventional tuned mass dampers (TMDs) with a pounding damping mechanism is demonstrated to be an efficient way for vibration control of flexible structures. In this paper, a double-tuned pendulum mass damper employing a pounding damping mechanism (DTPMD-PD) is proposed. DTPMD-PD dissipates energy through the collision between distributed balls with a smaller mass and viscoelastic (VE) boundary, which can effectively reduce noise during operation compared to conventional impact dampers. Moreover, DTPMD-PD utilizes a double-tuning mechanism, and its control performance is significantly enhanced. The motion equations of a multiple degree of freedom (MDOF) structure equipped with DTPMD-PD are formulated. Based on the H∞ optimization criterion, a numerical optimization is performed to obtain the optimal design parameters of DTPMD-PD. Additionally, the pounding dissipation capacity and the parametric identification of the impact force model are investigated through free pounding experiments, and the control performance and robustness of DTPMD-PD are experimentally studied in the laboratory. The results show that the proposed numerical modeling method has considerable accuracy through experimental verifications. The restitution coefficient of the pounding layer has a significant influence on the performance of proposed DTPMD-PD. Optimized DTPMD-PD has better effectiveness than conventional TMDs under harmonic and seismic loads.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"38 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76583030","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}
Gabriele Dessena, M. Civera, L. Zanotti Fragonara, Dmitry I. Ignatyev, J. Whidborne
Data-driven structural health monitoring (SHM) requires precise estimates of the target system behaviour. In this sense, SHM by means of modal parameters is strictly linked to system identification (SI). However, existing frequency-domain SI techniques have several theoretical and practical drawbacks. This paper proposes using an input-output system identification technique based on rational interpolation, known as the Loewner framework (LF), to estimate the modal properties of mechanical systems. Pioneeringly, the Loewner framework mode shapes and natural frequencies estimated by LF are then applied as damage-sensitive features for damage detection. To assess its capability, the Loewner framework is validated on both numerical and experimental datasets and compared to established system identification techniques. Promising results are achieved in terms of accuracy and reliability.
{"title":"A Loewner-Based System Identification and Structural Health Monitoring Approach for Mechanical Systems","authors":"Gabriele Dessena, M. Civera, L. Zanotti Fragonara, Dmitry I. Ignatyev, J. Whidborne","doi":"10.1155/2023/1891062","DOIUrl":"https://doi.org/10.1155/2023/1891062","url":null,"abstract":"Data-driven structural health monitoring (SHM) requires precise estimates of the target system behaviour. In this sense, SHM by means of modal parameters is strictly linked to system identification (SI). However, existing frequency-domain SI techniques have several theoretical and practical drawbacks. This paper proposes using an input-output system identification technique based on rational interpolation, known as the Loewner framework (LF), to estimate the modal properties of mechanical systems. Pioneeringly, the Loewner framework mode shapes and natural frequencies estimated by LF are then applied as damage-sensitive features for damage detection. To assess its capability, the Loewner framework is validated on both numerical and experimental datasets and compared to established system identification techniques. Promising results are achieved in terms of accuracy and reliability.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86504817","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}
Bridge deformation response data are the basis for calculating the dynamic parameters of the bridge, and it is of great significance to accurately measure the deformation response of the bridge during the load test and service conditions. A bridge deformation measurement method using an unmanned aerial system (UAS) with dual cameras and a deep learning-based object tracking method is proposed to measure the bridge deformation. The contributions are as follows: (1) To address the problem that the movement of the UAS brings error to the deformation measurement results, dual cameras with telephoto and wide-angle lenses are used to simultaneously capture the deformed points and stable points on the bridge, so as to simultaneously measure the deformation of the bridge and the displacement of the UAS, and then the displacement of UAS is eliminated by using the homography relationship between the two cameras. (2) To solve the problem that the traditional digital image correlation-based displacement measurement method is easily disturbed by factors such as light changes and occlusion, a displacement calculation method based on object detection network and target tracking algorithm is proposed to achieve the stable target displacement measurement. Finally, the proposed method was verified in a laboratory test and applied to the deformation measurement of an in-service bridge to verify the practicability of the proposed method.
{"title":"Bridge Deformation Measurement Using Unmanned Aerial Dual Camera and Learning-Based Tracking Method","authors":"Shang Jiang, Jian Zhang, Chenhao Gao","doi":"10.1155/2023/4752072","DOIUrl":"https://doi.org/10.1155/2023/4752072","url":null,"abstract":"Bridge deformation response data are the basis for calculating the dynamic parameters of the bridge, and it is of great significance to accurately measure the deformation response of the bridge during the load test and service conditions. A bridge deformation measurement method using an unmanned aerial system (UAS) with dual cameras and a deep learning-based object tracking method is proposed to measure the bridge deformation. The contributions are as follows: (1) To address the problem that the movement of the UAS brings error to the deformation measurement results, dual cameras with telephoto and wide-angle lenses are used to simultaneously capture the deformed points and stable points on the bridge, so as to simultaneously measure the deformation of the bridge and the displacement of the UAS, and then the displacement of UAS is eliminated by using the homography relationship between the two cameras. (2) To solve the problem that the traditional digital image correlation-based displacement measurement method is easily disturbed by factors such as light changes and occlusion, a displacement calculation method based on object detection network and target tracking algorithm is proposed to achieve the stable target displacement measurement. Finally, the proposed method was verified in a laboratory test and applied to the deformation measurement of an in-service bridge to verify the practicability of the proposed method.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83279575","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}
Yantao Zhu, Zhiduan Zhang, C. Gu, Yangtao Li, Kang Zhang, Mingxia Xie
Grasping the change behavior of dam foundation seepage pressure is of great significance for ensuring the safety of concrete dams. Because of the environmental complexity of the dam location, the prototypical seepage pressure data are easy to be contaminated by noise, which brings challenges to accurate prediction. Traditional denoising methods will lose the detailed characteristics of the objects, resulting in prediction models with limited flexibility and prediction accuracy. To address these problems, the prototypical data with noise are denoised using the variational mode decomposition (VMD)-wavelet packet denoising method. Then, an improved temporal convolutional network (ITCN) model is built for dam foundation seepage pressure data prediction. A hysteresis experiment is carried out to optimize the model structure by correlating the receptive field size of the ITCN model with the hysteresis of the dam foundation seepage pressure. Finally, the optimal ITCN dam foundation seepage pressure prediction model of each measurement point is obtained after the training. Three state-of-the-art methods in dam seepage monitoring are used as benchmark methods to compare the prediction performance of the proposed method. Four evaluation indicators are introduced to quantitatively evaluate and compare the prediction performance of the proposed method. The experimental results prove that the proposed method achieves high prediction accuracy flexibility. The indicator values of the ITCN model are only 50%–90% of those of LSTM and RNN models and 15%–40% of those of the stepwise regression model, and the values are all small.
{"title":"A Coupled Model for Dam Foundation Seepage Behavior Monitoring and Forecasting Based on Variational Mode Decomposition and Improved Temporal Convolutional Network","authors":"Yantao Zhu, Zhiduan Zhang, C. Gu, Yangtao Li, Kang Zhang, Mingxia Xie","doi":"10.1155/2023/3879096","DOIUrl":"https://doi.org/10.1155/2023/3879096","url":null,"abstract":"Grasping the change behavior of dam foundation seepage pressure is of great significance for ensuring the safety of concrete dams. Because of the environmental complexity of the dam location, the prototypical seepage pressure data are easy to be contaminated by noise, which brings challenges to accurate prediction. Traditional denoising methods will lose the detailed characteristics of the objects, resulting in prediction models with limited flexibility and prediction accuracy. To address these problems, the prototypical data with noise are denoised using the variational mode decomposition (VMD)-wavelet packet denoising method. Then, an improved temporal convolutional network (ITCN) model is built for dam foundation seepage pressure data prediction. A hysteresis experiment is carried out to optimize the model structure by correlating the receptive field size of the ITCN model with the hysteresis of the dam foundation seepage pressure. Finally, the optimal ITCN dam foundation seepage pressure prediction model of each measurement point is obtained after the training. Three state-of-the-art methods in dam seepage monitoring are used as benchmark methods to compare the prediction performance of the proposed method. Four evaluation indicators are introduced to quantitatively evaluate and compare the prediction performance of the proposed method. The experimental results prove that the proposed method achieves high prediction accuracy flexibility. The indicator values of the ITCN model are only 50%–90% of those of LSTM and RNN models and 15%–40% of those of the stepwise regression model, and the values are all small.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89286063","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}
Hong Zhang, Xiaotao Ma, Hejing Jiang, Kai Tong, Yu Zheng, J. Zhou
To accurately evaluate the overall corrosion degree of reinforced concrete (RC) beams, on the basis of the SMFL technology, the overall random corrosion detection experiment of six RC beams was carried out. The relationship between the tangential component By and the normal component Bz of the magnetic induction intensity and corrosion degree was analyzed, and a multidefect magnetic dipole model was established. The correlation between the average corrosion ratio C of the RC beam and the magnetic characteristic index KG was emphatically explored. The results showed that, with the increase in the average corrosion ratio C, the magnetic characteristic index KG showed an increasing trend as a whole. The index KG could weaken the influence of different historical magnetizations, but it had a certain dispersion. On the basis of the correlation and the Naive Bayesian model, the average corrosion ratio C was divided into four grades. The probability of C falling in different value ranges can be quantitatively evaluated using the KG magnetic characteristic index. The reliability is as high as 97.4% and as low as 56.8% so as to realize the quantitative grading evaluation of the corrosion of the rebar in the RC beam.
{"title":"Grading Evaluation of Overall Corrosion Degree of Corroded RC Beams via SMFL Technique","authors":"Hong Zhang, Xiaotao Ma, Hejing Jiang, Kai Tong, Yu Zheng, J. Zhou","doi":"10.1155/2023/6672823","DOIUrl":"https://doi.org/10.1155/2023/6672823","url":null,"abstract":"To accurately evaluate the overall corrosion degree of reinforced concrete (RC) beams, on the basis of the SMFL technology, the overall random corrosion detection experiment of six RC beams was carried out. The relationship between the tangential component By and the normal component Bz of the magnetic induction intensity and corrosion degree was analyzed, and a multidefect magnetic dipole model was established. The correlation between the average corrosion ratio C of the RC beam and the magnetic characteristic index KG was emphatically explored. The results showed that, with the increase in the average corrosion ratio C, the magnetic characteristic index KG showed an increasing trend as a whole. The index KG could weaken the influence of different historical magnetizations, but it had a certain dispersion. On the basis of the correlation and the Naive Bayesian model, the average corrosion ratio C was divided into four grades. The probability of C falling in different value ranges can be quantitatively evaluated using the KG magnetic characteristic index. The reliability is as high as 97.4% and as low as 56.8% so as to realize the quantitative grading evaluation of the corrosion of the rebar in the RC beam.","PeriodicalId":22049,"journal":{"name":"Structural Control and Health Monitoring","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89502155","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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