The structural dynamic response reconstruction technology can extract unmeasured information from limited measured data,significantly impacting vibration control,load identification,parameter identification,fault diag...The structural dynamic response reconstruction technology can extract unmeasured information from limited measured data,significantly impacting vibration control,load identification,parameter identification,fault diagnosis,and related fields.This paper proposes a dynamic response reconstruction method based on the Kalman filter,which simultaneously identifies external excitation and reconstructs dynamic responses at unmeasured positions.The weighted least squares method determines the load weighting matrix for excitation identification,while the minimum variance unbiased estimation determines the Kalman filter gain.The excitation prediction Kalman filter is constructed through time,excitation,and measurement updates.Subsequently,the response at the target point is reconstructed using the state vector,observation matrix,and excitation influence matrix obtained through the excitation prediction Kalman filter algorithm.An algorithm for reconstructing responses in continuous system using the excitation prediction Kalman filtering algorithm in modal space is derived.The proposed structural dynamic response reconstruction method evaluates the response reconstruction and the load identification performance under various load types and errors through simulation examples.Results demonstrate the accurate excitation identification under different load conditions and simultaneous reconstruction of target point responses,verifying the feasibility and reliability of the proposed method.展开更多
Lost acceleration response reconstruction is crucial for assessing structural conditions in structural health monitoring(SHM).However,traditional methods struggle to address the reconstruction of acceleration response...Lost acceleration response reconstruction is crucial for assessing structural conditions in structural health monitoring(SHM).However,traditional methods struggle to address the reconstruction of acceleration responses with complex features,resulting in a lower reconstruction accuracy.This paper addresses this challenge by leveraging the advanced feature extraction and learning capabilities of fully convolutional networks(FCN)to achieve precise reconstruction of acceleration responses.In the designed network architecture,the incorporation of skip connections preserves low-level details of the network,greatly facilitating the flow of information and improving training efficiency and accuracy.Dropout techniques are employed to reduce computational load and enhance feature extraction.The proposed FCN model automatically extracts high-level features from the input data and establishes a nonlinearmapping relationship between the input and output responses.Finally,the accuracy of the FCN for structural response reconstructionwas evaluated using acceleration data from an experimental arch rib and comparedwith several traditional methods.Additionally,this approach was applied to reconstruct actual acceleration responses measured by an SHM system on a long-span bridge.Through parameter analysis,the feasibility and accuracy of aspects such as available response positions,the number of available channels,and multi-channel response reconstruction were explored.The results indicate that this method exhibits high-precision response reconstruction capability in both time and frequency domains.,with performance surpassing that of other networks,confirming its effectiveness in reconstructing responses under various sensor data loss scenarios.展开更多
Estimation of lateral displacement and acceleration responses is essential to assess safety and serviceability of high-rise buildings under dynamic loadings including earthquake excitations. However, the measurement i...Estimation of lateral displacement and acceleration responses is essential to assess safety and serviceability of high-rise buildings under dynamic loadings including earthquake excitations. However, the measurement information from the limited number of sensors installed in a building structure is often insufficient for the complete structural performance assessment. An integrated multi-type sensor placement and response reconstruction method has thus been proposed by the authors to tackle this problem. To validate the feasibility and effectiveness of the proposed method, an experimental investigation using a cantilever beam with multi-type sensors is performed and reported in this paper. The experimental setup is first introduced. The finite element modelling and model updating of the cantilever beam are then performed. The optimal sensor placement for the best response reconstruction is determined by the proposed method based on the updated FE model of the beam. After the sensors are installed on the physical cantilever beam, a number of experiments are carried out. The responses at key locations are reconstructed and compared with the measured ones. The reconstructed responses achieve a good match with the measured ones, manifesting the feasibility and effectiveness of the proposed method. Besides, the proposed method is also examined for the cases of different excitations and unknown excitation, and the results prove the proposed method to be robust and effective. The superiority of the optimized sensor placement scheme is finally demonstrated through comparison with two other different sensor placement schemes： the accelerometer-only scheme and non-optimal sensor placement scheme. The proposed method can be applied to high-rise buildings for seismic performance assessment.展开更多
In structural health monitoring(SHM),the measurement is point-wise but structures are continuous.Thus,input estimation has become a hot research subject with which the full-field structural response can be calculated ...In structural health monitoring(SHM),the measurement is point-wise but structures are continuous.Thus,input estimation has become a hot research subject with which the full-field structural response can be calculated with a finite element model(FEM).This paper proposes a framework based on the dynamic stiffness theory,to estimate harmonic input,reconstruct responses,and to localize damages from seriously deficient measurements.To begin,Fourier transform converts the dynamic equilibrium equation to an equivalent static one in the frequency domain,which is underdetermined since the dimension of measurement vector is far less than the FEM-node number.The principal component analysis has been adopted to“compress”the under-determined equation,and formed an over-determined equation to estimate the unknown input.Then,inverse Fourier transform converts the estimated input in the frequency domain to the time domain.Applying this to the FEM can reconstruct the target responses.If a structure is damaged,the estimated nodal force can localize the damage.To improve the damage-detection accuracy,a multi-measurement-based indicator has been proposed.Numerical simulations have validated that the proposed framework can capably estimate input and reconstruct multi-types of full-field responses,and the damage indicator can localize minor damages even with the existence of noise.展开更多
Recently, Sandia Laboratories developed a neutron scatter camera to detect special nuclear materials. This camera exhibits the following advantages: high efficiency, direction discrimination, neutron-gamma discriminat...Recently, Sandia Laboratories developed a neutron scatter camera to detect special nuclear materials. This camera exhibits the following advantages: high efficiency, direction discrimination, neutron-gamma discrimination ability, and wide field of view. However, using the direct projection method, the angular resolution of this camera is limited by uncertainties in the energies estimated from pulse height and time of flight measurements. In this study, we established an eight-element neutron scatter camera and conducted the experiment with a ^(252)Cf neutron source. The results show that it has an angular resolution better than 8°(1s) and a detection efficiency of approximately 2.6′10-4. Using maximum likelihood expectation maximization method, the image artifact was eliminated, and the angular resolution was improved. We proposed an average scattering angle method to estimate the scattering energy of neutrons and Compton gamma rays. As such, we can obtain a recognizable image and energy spectrum of the source with some degradation of energy and image resolutions. Finally, a newly measured light response function based on the MPD^(-4) device was used for image reconstruction. Although we did not obtain a better result than that of the standard light response function, we have observed the effects of light response function on image reconstruction.展开更多
基金supported by the National Natural Science Foundation of China(Nos.12372066,U23B6009,52171261)the Aeronautical Science Fund(No.20240013052002)the Qing Lan Project。
文摘The structural dynamic response reconstruction technology can extract unmeasured information from limited measured data,significantly impacting vibration control,load identification,parameter identification,fault diagnosis,and related fields.This paper proposes a dynamic response reconstruction method based on the Kalman filter,which simultaneously identifies external excitation and reconstructs dynamic responses at unmeasured positions.The weighted least squares method determines the load weighting matrix for excitation identification,while the minimum variance unbiased estimation determines the Kalman filter gain.The excitation prediction Kalman filter is constructed through time,excitation,and measurement updates.Subsequently,the response at the target point is reconstructed using the state vector,observation matrix,and excitation influence matrix obtained through the excitation prediction Kalman filter algorithm.An algorithm for reconstructing responses in continuous system using the excitation prediction Kalman filtering algorithm in modal space is derived.The proposed structural dynamic response reconstruction method evaluates the response reconstruction and the load identification performance under various load types and errors through simulation examples.Results demonstrate the accurate excitation identification under different load conditions and simultaneous reconstruction of target point responses,verifying the feasibility and reliability of the proposed method.
基金National Natural Science Foundation of China(Grant Nos.52408314,52278292)Chongqing Outstanding Youth Science Foundation(Grant No.CSTB2023NSCQ-JQX0029)+1 种基金Science and Technology Project of Sichuan Provincial Transportation Department(Grant No.2023-ZL-03)Science and Technology Project of Guizhou Provincial Transportation Department(Grant No.2024-122-018).
文摘Lost acceleration response reconstruction is crucial for assessing structural conditions in structural health monitoring(SHM).However,traditional methods struggle to address the reconstruction of acceleration responses with complex features,resulting in a lower reconstruction accuracy.This paper addresses this challenge by leveraging the advanced feature extraction and learning capabilities of fully convolutional networks(FCN)to achieve precise reconstruction of acceleration responses.In the designed network architecture,the incorporation of skip connections preserves low-level details of the network,greatly facilitating the flow of information and improving training efficiency and accuracy.Dropout techniques are employed to reduce computational load and enhance feature extraction.The proposed FCN model automatically extracts high-level features from the input data and establishes a nonlinearmapping relationship between the input and output responses.Finally,the accuracy of the FCN for structural response reconstructionwas evaluated using acceleration data from an experimental arch rib and comparedwith several traditional methods.Additionally,this approach was applied to reconstruct actual acceleration responses measured by an SHM system on a long-span bridge.Through parameter analysis,the feasibility and accuracy of aspects such as available response positions,the number of available channels,and multi-channel response reconstruction were explored.The results indicate that this method exhibits high-precision response reconstruction capability in both time and frequency domains.,with performance surpassing that of other networks,confirming its effectiveness in reconstructing responses under various sensor data loss scenarios.
基金The Hong Kong Polytechnic University through the group project "Fundamentals of Earthquake Engineering for Hong Kong"(4-ZZCD)the collaborative research project with Beijing University of Technology(4-ZZGD)
文摘Estimation of lateral displacement and acceleration responses is essential to assess safety and serviceability of high-rise buildings under dynamic loadings including earthquake excitations. However, the measurement information from the limited number of sensors installed in a building structure is often insufficient for the complete structural performance assessment. An integrated multi-type sensor placement and response reconstruction method has thus been proposed by the authors to tackle this problem. To validate the feasibility and effectiveness of the proposed method, an experimental investigation using a cantilever beam with multi-type sensors is performed and reported in this paper. The experimental setup is first introduced. The finite element modelling and model updating of the cantilever beam are then performed. The optimal sensor placement for the best response reconstruction is determined by the proposed method based on the updated FE model of the beam. After the sensors are installed on the physical cantilever beam, a number of experiments are carried out. The responses at key locations are reconstructed and compared with the measured ones. The reconstructed responses achieve a good match with the measured ones, manifesting the feasibility and effectiveness of the proposed method. Besides, the proposed method is also examined for the cases of different excitations and unknown excitation, and the results prove the proposed method to be robust and effective. The superiority of the optimized sensor placement scheme is finally demonstrated through comparison with two other different sensor placement schemes： the accelerometer-only scheme and non-optimal sensor placement scheme. The proposed method can be applied to high-rise buildings for seismic performance assessment.
基金support for the work reported in this paper from the National Natural Science Foundation of China(Grant No.51878482)the Hong Kong(China)Scholars Program(No.XJ2021036)and State Key Laboratory of Disaster Reduction in Civil Engineering,Tongji University(No.SLDRCE15-A-02).
文摘In structural health monitoring(SHM),the measurement is point-wise but structures are continuous.Thus,input estimation has become a hot research subject with which the full-field structural response can be calculated with a finite element model(FEM).This paper proposes a framework based on the dynamic stiffness theory,to estimate harmonic input,reconstruct responses,and to localize damages from seriously deficient measurements.To begin,Fourier transform converts the dynamic equilibrium equation to an equivalent static one in the frequency domain,which is underdetermined since the dimension of measurement vector is far less than the FEM-node number.The principal component analysis has been adopted to“compress”the under-determined equation,and formed an over-determined equation to estimate the unknown input.Then,inverse Fourier transform converts the estimated input in the frequency domain to the time domain.Applying this to the FEM can reconstruct the target responses.If a structure is damaged,the estimated nodal force can localize the damage.To improve the damage-detection accuracy,a multi-measurement-based indicator has been proposed.Numerical simulations have validated that the proposed framework can capably estimate input and reconstruct multi-types of full-field responses,and the damage indicator can localize minor damages even with the existence of noise.
基金supported by the National Natural Science Fundation of China(Grant Nos.1110510611375144&11275153)
文摘Recently, Sandia Laboratories developed a neutron scatter camera to detect special nuclear materials. This camera exhibits the following advantages: high efficiency, direction discrimination, neutron-gamma discrimination ability, and wide field of view. However, using the direct projection method, the angular resolution of this camera is limited by uncertainties in the energies estimated from pulse height and time of flight measurements. In this study, we established an eight-element neutron scatter camera and conducted the experiment with a ^(252)Cf neutron source. The results show that it has an angular resolution better than 8°(1s) and a detection efficiency of approximately 2.6′10-4. Using maximum likelihood expectation maximization method, the image artifact was eliminated, and the angular resolution was improved. We proposed an average scattering angle method to estimate the scattering energy of neutrons and Compton gamma rays. As such, we can obtain a recognizable image and energy spectrum of the source with some degradation of energy and image resolutions. Finally, a newly measured light response function based on the MPD^(-4) device was used for image reconstruction. Although we did not obtain a better result than that of the standard light response function, we have observed the effects of light response function on image reconstruction.
