The determination of the dynamic load is one of the indispensable technologies for structure design and health monitoring for aerospace vehicles.However,it is a significant challenge to measure the external excitation...The determination of the dynamic load is one of the indispensable technologies for structure design and health monitoring for aerospace vehicles.However,it is a significant challenge to measure the external excitation directly.By contrast,the technique of dynamic load identification based on the dynamic model and the response information is a feasible access to obtain the dynamic load indirectly.Furthermore,there are multi-source uncertainties which cannot be neglected for complex systems in the load identification process,especially for aerospace vehicles.In this paper,recent developments in the dynamic load identification field for aerospace vehicles considering multi-source uncertainties are reviewed,including the deterministic dynamic load identification and uncertain dynamic load identification.The inversion methods with different principles of concentrated and distributed loads,and the quantification and propagation analysis for multi-source uncertainties are discussed.Eventually,several possibilities remaining to be explored are illustrated in brief.展开更多
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
Based on the platform of Matlab and the theory of digital signal processing, we propose a method in the cepstrum domain for dynamic load spectra identification of machinery. We demonstrate that the dynamic load spectr...Based on the platform of Matlab and the theory of digital signal processing, we propose a method in the cepstrum domain for dynamic load spectra identification of machinery. We demonstrate that the dynamic load spectra can be identified from the response signal of the system, based on cepstra. An ARMA model is built based on the harmonic retrieval by high-order spectra. The coefficients of a Green function are determined and the window width can be estimated. Finally the effectiveness of the method is validated by simulation results.展开更多
基金supported by the National Nature Science Foundation of China(No.12072007)the Ningbo Nature Science Foundation(No.202003N4018)+1 种基金the Aeronautical Science Foundation of China (No. 20182951014)the Defense Industrial Technology Development Program(No.JCKY2019209C004)
文摘The determination of the dynamic load is one of the indispensable technologies for structure design and health monitoring for aerospace vehicles.However,it is a significant challenge to measure the external excitation directly.By contrast,the technique of dynamic load identification based on the dynamic model and the response information is a feasible access to obtain the dynamic load indirectly.Furthermore,there are multi-source uncertainties which cannot be neglected for complex systems in the load identification process,especially for aerospace vehicles.In this paper,recent developments in the dynamic load identification field for aerospace vehicles considering multi-source uncertainties are reviewed,including the deterministic dynamic load identification and uncertain dynamic load identification.The inversion methods with different principles of concentrated and distributed loads,and the quantification and propagation analysis for multi-source uncertainties are discussed.Eventually,several possibilities remaining to be explored are illustrated in brief.
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Project 59775004 supported by National Natural Science Foundation of China
文摘Based on the platform of Matlab and the theory of digital signal processing, we propose a method in the cepstrum domain for dynamic load spectra identification of machinery. We demonstrate that the dynamic load spectra can be identified from the response signal of the system, based on cepstra. An ARMA model is built based on the harmonic retrieval by high-order spectra. The coefficients of a Green function are determined and the window width can be estimated. Finally the effectiveness of the method is validated by simulation results.
