In this paper a method of aerodynamic parameter identification of vehicle, the maximum likelihood method, is introduced. The aerodynamic model of vehicle is identified and the basic equations using maximum likelihood ...In this paper a method of aerodynamic parameter identification of vehicle, the maximum likelihood method, is introduced. The aerodynamic model of vehicle is identified and the basic equations using maximum likelihood method are established. After that, the simulation data is identified to verify the correctness of the mathematic model and identification method. Last, the practical flight data is identified and analyzed.展开更多
The identification of aerodynamic parameters is accomplished through the test data of the dynamic movement of scaled aircraft models flying dynamically in wind tunnel,which can real-ize the accurate acquisition of the...The identification of aerodynamic parameters is accomplished through the test data of the dynamic movement of scaled aircraft models flying dynamically in wind tunnel,which can real-ize the accurate acquisition of the aerodynamic model of the aircraft in the preliminary stage for aircraft design,and it is of great significance for improving the efficiency of aircraft design.How-ever,the translational motion of the test model in the wind tunnel virtual flight is subject to con-straints that result in distinct flight dynamics compared to free flight.These constraints have implications for the accuracy of aerodynamic derivatives obtained through the identification of wind tunnel test data.With this issue in mind,the research studies the differences in longitudinal dynamic characteristics between unconstrained free flight and wind tunnel virtual flight,and inno-vatively proposes an online correction test based wind tunnel virtual flight test technique.The lon-gitudinal trajectory and velocity changes of the model are solved online by the aerodynamic forces measured during the test,and then the coupled relationship between aircraft translation and rota-tion is used to correct the model's pitch attitude motion online.For the first time,the problem of solving the data approximation for free flight has been solved,eliminating the difference between the dynamics of wind tunnel virtual flight and free flight,and improving the accuracy of the aero-dynamic derivative identification results.The experiment's findings show that accurate aerodynamic derivatives can be identified based on the online correction test data,and the observed behaviour of the identified motion model has similarities to that of the free flight motion model.展开更多
To achieve the manufacturing of Thin-Wall and High-Rib Components(TWHRC)with high precision,a novel heavy load Multi-DOF Envelope Forming Press(MEFP)with Parallel Kinematic Mechanism(PKM),driven by six Permanent Magne...To achieve the manufacturing of Thin-Wall and High-Rib Components(TWHRC)with high precision,a novel heavy load Multi-DOF Envelope Forming Press(MEFP)with Parallel Kinematic Mechanism(PKM),driven by six Permanent Magnet Synchronous Motors(PMSMs),is developed.However,on account of the heavy forming load,the PMSM parameters are in great variation.Meanwhile,the PMSM is always in a transient state caused by fast time-varying forming load,resulting in low identification precision of varied PMSM parameters and control precision of PMSM under traditional parameter identification methods.To solve this problem,a novel Sliding Mode Control Method with Enhanced PMSM Parameter Identification(SMCMEPPI)for heavy load MEFP is proposed.Firstly,the kinematic model of MEFP is established.Secondly,the variation law of PMSM parameters under heavy load is revealed.Thirdly,an enhanced PMSM parameter identification method is proposed,in which the q axis current of PMSM is used to represent the changing rate of forming load and the adjustment factor is first proposed to remove improper input of PMSM parameter identification online.Fourthly,the Electromechanical Coupling Dynamic Model(ECDM)of MEFP,which includes identified PMSM parameters,is developed.Finally,based on the developed ECDM,a novel SMCMEPPI is proposed to realize the high-precision control of heavy load MEFP.The experimental results indicate that the proposed SMCMEPPI can significantly improve the control precision of heavy load MEFP.展开更多
A new identification method is proposed to solve the problem of the influence on the loaded excitation signals brought by high feedback gain augmentation in lateral-directional aerodynamic parameters identification of...A new identification method is proposed to solve the problem of the influence on the loaded excitation signals brought by high feedback gain augmentation in lateral-directional aerodynamic parameters identification of fly-by-wire（FBW） passenger airliners. Taking for example an FBW passenger airliner model with directional relaxed-static-stability, through analysis of its signal energy distribution and airframe frequency response, a new method is proposed for signal type selection, signal parameters design, and the appropriate frequency relationship between the aileron and rudder excitation signals. A simulation validation is presented of the FBW passenger airliner＇s lateral-directional aerodynamic parameters identification. The validation result demonstrates that the designed signal can excite the lateral-directional motion mode of the FBW passenger airliner adequately and persistently. Meanwhile, the relative errors of aerodynamic parameters are less than 5%.展开更多
In this paper, the problem of time-varying aerodynamic parameters identification under measurement noises is studied. By analyzing the key aerodynamic parameters that affect the aircraft control system, a system model...In this paper, the problem of time-varying aerodynamic parameters identification under measurement noises is studied. By analyzing the key aerodynamic parameters that affect the aircraft control system, a system model with extended states for identifying equivalent aerodynamic parameters is established, and error parameters are extended to the system state, avoiding the difficulty caused by the unknown dynamic in the system. Furthermore, an identification algorithm based on extended state Kalman filter is designed, and it is proved that the algorithm has quasi-consistency, thus, the estimation error can be evaluated in real time. Finally, the simulation results under typical flight scenarios show that the designed algorithm can accurately identify aerodynamic parameters, and has desired convergence speed and convergence precision.展开更多
To overcome the limitations of low efficiency and reliance on manual processes in the measurement of geometric parameters for bridge prefabricated components,a method based on deep learning and computer vision is deve...To overcome the limitations of low efficiency and reliance on manual processes in the measurement of geometric parameters for bridge prefabricated components,a method based on deep learning and computer vision is developed to identify the geometric parameters.The study utilizes a common precast element for highway bridges as the research subject.First,edge feature points of the bridge component section are extracted from images of the precast component cross-sections by combining the Canny operator with mathematical morphology.Subsequently,a deep learning model is developed to identify the geometric parameters of the precast components using the extracted edge coordinates from the images as input and the predefined control parameters of the bridge section as output.A dataset is generated by varying the control parameters and noise levels for model training.Finally,field measurements are conducted to validate the accuracy of the developed method.The results indicate that the developed method effectively identifies the geometric parameters of bridge precast components,with an error rate maintained within 5%.展开更多
To analyze a multibody system composed of non-uniform beam and spring-mass subsystems, the model discretization is carried on by utilizing the finite element method（FEM）, the dynamic model of non-uniform beam is dev...To analyze a multibody system composed of non-uniform beam and spring-mass subsystems, the model discretization is carried on by utilizing the finite element method（FEM）, the dynamic model of non-uniform beam is developed by using the transfer matrix method of multibody system（MS-TMM）, the transfer matrix of non-u- niform beam is derived, and the natural frequencies are computed. Compared with the numerical assembly method （NAM）, the results by MS-TMM have good agreement with the results by FEM, and are better than the results by NAM. When using the high precision method, the global dynamic equations of the complex multibody system are not needed and the orders of involved system matrices are decreased greatly. For the investigation on the re- verse problem of the physical parameter identification of multibody system, MS-TMM and the optimization tech- nology based on genetic algorithms（GAs） are combined and extended. The identification problem is exchanged for an optimization problem, and it is formulated as a global minimum solution of the objective function with respect to natural frequencies of multibody system. At last, the numerical example of non-uniform beam with attach- ments is discussed, and the identification results indicate the feasibility and the effectivity of the proposed aop- proach.展开更多
Accurate and reliable photovoltaic(PV)modeling is crucial for the performance evaluation,control,and optimization of PV systems.However,existing methods for PV parameter identification often suffer from limitations in...Accurate and reliable photovoltaic(PV)modeling is crucial for the performance evaluation,control,and optimization of PV systems.However,existing methods for PV parameter identification often suffer from limitations in accuracy and efficiency.To address these challenges,we propose an adaptive multi-learning cooperation search algorithm(AMLCSA)for efficient identification of unknown parameters in PV models.AMLCSA is a novel algorithm inspired by teamwork behaviors in modern enterprises.It enhances the original cooperation search algorithm in two key aspects:(i)an adaptive multi-learning strategy that dynamically adjusts search ranges using adaptive weights,allowing better individuals to focus on local exploitation while guiding poorer individuals toward global exploration;and(ii)a chaotic grouping reflection strategy that introduces chaotic sequences to enhance population diversity and improve search performance.The effectiveness of AMLCSA is demonstrated on single-diode,double-diode,and three PV-module models.Simulation results show that AMLCSA offers significant advantages in convergence,accuracy,and stability compared to existing state-of-the-art algorithms.展开更多
The complex geometrical features of mechanical components significantly influence contact interactions and system dynamics.However,directly modeling contact forces on surfaces with intricate geometries presents consid...The complex geometrical features of mechanical components significantly influence contact interactions and system dynamics.However,directly modeling contact forces on surfaces with intricate geometries presents considerable challenges.This study focuses on the helically twisted wire rope-sheave contact and proposes a contact force model that incorporates complex geometric features through a parameter identification approach.The model's impact on contact forces and system dynamics is thoroughly investigated.Leveraging a point contact model and an elliptic integral approximation,a loss function is formulated using the finite element(FE)contact model results as the reference data.Geometric parameters are subsequently determined by optimizing this loss function via a genetic algorithm(GA).The findings reveal that the contact stiffness increases with the wire rope pitch length,the radius of principal curvature,and the elliptic eccentricity of the contact zone.The proposed contact force model is integrated into a rigid-flexible coupled dynamics model,developed by the absolute node coordinate formulation,to examine the effects of contact geometry on system dynamics.The results demonstrate that the variations in wire rope geometry alter the contact stiffness,which in turn affects dynamic rope tension through frictional energy dissipation.The enhanced model's predictions exhibit superior alignment with the experimental data,thereby validating the methodology.This approach provides new insights for deducing the contact geometry from kinetic parameters and monitoring the performance degradation of mechanical components.展开更多
Abstract This paper describes a longitudinal parameter identification procedure for a small unmanned aerial vehicle （UAV） through modified particle swam optimization （PSO）. The proce- dure is demonstrated using a ...Abstract This paper describes a longitudinal parameter identification procedure for a small unmanned aerial vehicle （UAV） through modified particle swam optimization （PSO）. The proce- dure is demonstrated using a small UAV equipped with only an micro-electro-mechanical systems （MEMS） inertial mea,mring element and a global positioning system （GPS） receiver to provide test information. A small UAV longitudinal parameter mathematical model is derived and the modified method is proposed based on PSO with selective particle regeneration （SRPSO）. Once modified PSO is applied to the mathematical model, the simulation results show that the mathematical model is correct, and aerodynamic parameters and coefficients of the propeller can be identified accurately. Results are compared with those of PSO and SRPSO and the comparison shows that the proposed method is more robust and faster than the other methods for the longitudinal parameter identification of the small UAV. Some parameter identification results are affected slightly by noise, but the identification results are very good overall. Eventually, experimental validation is employed to test the proposed method, which demonstrates the usefulness of this method.展开更多
Modal parameters, including fundamental frequencies, damping ratios, and mode shapes, could be used to evaluate the health condition of structures. Automatic modal parameter identification, which plays an essential ro...Modal parameters, including fundamental frequencies, damping ratios, and mode shapes, could be used to evaluate the health condition of structures. Automatic modal parameter identification, which plays an essential role in realtime structural health monitoring, has become a popular topic in recent years. In this study, an automatic modal parameter identification procedure for high arch dams is proposed. The proposed procedure is implemented by combining the densitybased spatial clustering of applications with noise(DBSCAN) algorithm and the stochastic subspace identification(SSI). The 210-m-high Dagangshan Dam is investigated as an example to verify the feasibility of the procedure. The results show that the DBSCAN algorithm is robust enough to interpret the stabilization diagram from SSI and may avoid outline modes. This leads to the proposed procedure obtaining a better performance than the partitioned clustering and hierarchical clustering algorithms. In addition, the errors of the identified frequencies of the arch dam are within 4%, and the identified mode shapes are in agreement with those obtained from the finite element model, which implies that the proposed procedure is accurate enough to use in modal parameter identification. The procedure is feasible for online modal parameter identification and modal tracking of arch dams.展开更多
The flight control system of a fly-by-wire （FBW） passenger airliner with a complex frame-work and high feedback gain augmentation would change the original characteristic of a loaded signal and suppress the excitati...The flight control system of a fly-by-wire （FBW） passenger airliner with a complex frame-work and high feedback gain augmentation would change the original characteristic of a loaded signal and suppress the excitation of an airplane＇s pertinent motion modes. Taking a research example of an FBW passenger airliner model with longitudinal relaxed-static-stability, a new method of signal type selection and signal parameter design is proposed, through analysis of signal energy distribution and plane body＇s frequency response. According to CCAR60--the Appraisal and Use Regulation of Flight Simulator Device, the simulation validation of the FBW passenger airliner＇s longitudinal aerodynamic parameters identification is put forward. The validation result indicates that the designed signal could excite the longitudinal motion mode of the FBW passenger airliner adequately and the multiparameter comparison in simulation meets the objective test request of CCAR60. Meanwhile, the relative errors of aerodynamic parameters are less than 10%.展开更多
Operational Modal Analysis(OMA) refers to the modal analysis of a structure in its operating state. The advantage of OMA is that only the output vibration signal of a system is used in the analysis process. Classic OM...Operational Modal Analysis(OMA) refers to the modal analysis of a structure in its operating state. The advantage of OMA is that only the output vibration signal of a system is used in the analysis process. Classic OMA is based on the white noise excitation assumption and many identification methods have been developed in both time domain and frequency domain. But in reality, many environmental excitations are not compliance with the white noise assumption. In this paper, a method of half power bandwidth analysis is applied to power spectrum analysis to deal with the colored noise and trapezoidal spectral excitation. The modal frequencies and modal damping ratios are derived and the error caused by trapezoidal spectral and colored noise excitation are analyzed. It is proved that the OMA algorithm based on the white noise assumption can be extended to the colored noise environments under certain conditions. Finally, a simulation example with a cantilever beam and a vibration test with four kinds of colored noise and trapezoidal spectrum base excitation are carried out and the results support the proposed method.展开更多
In this paper,a time–frequency algorithm based on adaptive chirplet transform for parameter modeling and identification of Linear Time-Varying(LTV)systems under random excitation is presented.It is assumed that the s...In this paper,a time–frequency algorithm based on adaptive chirplet transform for parameter modeling and identification of Linear Time-Varying(LTV)systems under random excitation is presented.It is assumed that the solution of responses of LTV structures is expressed as the sum of multicomponent Linear Frequency Modulated(LFM)signals in a short-time.Then the measured acceleration response is used to perform the adaptive chirplet transform,in which an integral algorithm is employed to reconstruct the velocity and displacement responses.The vibration differential equation with time-varying coefficients is transformed into a simple linear equation.Furthermore,for systems under random excitation,the input–output relation based on correlation function is also derived to estimate the parameters including physicals parameters and instantaneous modal parameters.The full procedure of the method is presented and validated by using simulated responses.The results show that the presented method is accurate and robust for various LTV systems under random excitation.展开更多
Offshore platforms are susceptible to structural damage due to prolonged exposure to random loads,such as wind,waves,and currents.This is particularly true for platforms that have been in service for an extended perio...Offshore platforms are susceptible to structural damage due to prolonged exposure to random loads,such as wind,waves,and currents.This is particularly true for platforms that have been in service for an extended period.Identifying the modal parameters of offshore platforms is crucial for damage diagno sis,as it serves as a prerequisite and foundation for the process.Therefore,it holds great significance to prioritize the identification of these parameters.Aiming at the shortcomings of the traditional Fast Bayesian Fast Fourier Transform(FBFFT) method,this paper proposes a modal parameter identification method based on Automatic Frequency Domain Decomposition(AFDD) and optimized FBFFT.By introducing the AFDD method and Powell optimization algorithm,this method can automatically identify the initial value of natural frequency and solve the objective function efficiently and simply.In order to verify the feasibility and effectiveness of the proposed method,it is used to identify the modal parameters of the IASC-ASCE benchmark model and the j acket platform structure model,and the Most Probable Value(MPV) of the modal parameters and their respective posterior uncertainties are successfully identified.The identification results of the IASC-ASCE benc hmark model are compared with the identification re sults of the MODE-ID method,which verifies the effectivene ss and accuracy of the proposed method for identifying modal parameters.It provides a simple and feasible method for quantifying the influence of uncertain factors such as environmental parameters on the identification results,and also provide s a reference for modal parameter identification of other large structures.展开更多
The problem of how to identify the piecewise affine system is studied in this paper, where this considered piecewise affine system is a special nonlinear system. The reason why it is not easy to identify this piecewis...The problem of how to identify the piecewise affine system is studied in this paper, where this considered piecewise affine system is a special nonlinear system. The reason why it is not easy to identify this piecewise affine system is that each separated region and each unknown parameter vector are all needed to be determined simultaneously. Then, firstly, in order to achieve the identification goal, a multi-class classification process is proposed to determine each separated region. As the proposed multi-class classification process is the same with the classical data clustering strategy, the multi-class classification process can combine the first order algorithm of convex optimization, while achieving the goal of the classification process. Secondly, a zonotope parameter identification algorithm is used to construct a set, which contains the unknown parameter vector. In this zonotope parameter identification algorithm, the strict probabilistic description about the external noise is relaxed, and each unknown parameter vector is also identified. Furthermore, this constructed set is consistent with the measured output and the given bound corresponding to the noise. Thirdly, a sufficient condition about guaranteeing our derived zonotope not growing unbounded with iterations is formulated as an explicit linear matrix inequality. Finally, the effectiveness of this zonotope parameter identification algorithm is proven through a simulation example.展开更多
In the actual measurement of offshore wind turbines(OWTs),the measured accelerations usually contain a large amount of noise due to the complex and harsh marine environment,which is not conducive to the identification...In the actual measurement of offshore wind turbines(OWTs),the measured accelerations usually contain a large amount of noise due to the complex and harsh marine environment,which is not conducive to the identification of structural modal parameters.For OWTs with remarkably low structural modal frequencies,displacements can effectively suppress the high-frequency vibration noise and amplify the low-frequency vibration of the structure.However,finding a reference point to measure structural displacements at sea is difficult.Therefore,only a few studies on the use of dynamic displacements to identify the modal parameters of OWTs with high-pile foundations are available.Hence,this paper develops a displacement conversion strategy to study the modal parameter identification of OWTs with high-pile foundations.The developed strategy can be divided into the following three parts:zero-order correction of measured acceleration,high-pass filtering by the Butterworth polynomial,and modal parameter identification using the calculated displacement.The superiority of the proposed strategy is verified by analyzing a numerical OWT with a high-pile foundation and the measured accelerations from an OWT with a high-pile foundation.The results show that for OWTs with high-pile foundations dominated by low frequencies,the developed strategy of converting accelerations into displacements and then performing modal parameter identification is advantageous to the identification of modal parameters,and the results have high accuracy.展开更多
In order to identify aquifer parameter,authors develops an improved combinatorial method called best chromosome clone plus younger generation chromosome prepotency genetic algorithm (BCC-YGCP-GA), based on a decimal s...In order to identify aquifer parameter,authors develops an improved combinatorial method called best chromosome clone plus younger generation chromosome prepotency genetic algorithm (BCC-YGCP-GA), based on a decimal system simple genetic algorithm (SGA). The paper takes unsteady state flows in a two dimensional, inhomogeneous, confined aquifer for a ideal model, and utilizes SGA and BCC-YGCP-GA coupled to finite element method for identifying aquifer hydraulic conductivity K 1 ,K 2 ,K 3 and storage S 1 ,S 2 ,S 3 , respectively. It is shown from the result that GSA does not reach convergence with 100 generations, whereas convergence rate of BCC-YGCD-GA is very fast. Objective function value calculated by BCC-YGCD-GA is 0 001 29 with 100 generations, and hydraulic conductivity and storage of three zones are almost equal to the "true" values of ideal model.展开更多
A new simple and effective inertial parameter identification method based on sinusoidal vibrations of a six-degree-of-freedom parallel manipulator is proposed. Compared with previously known identification algorithms,...A new simple and effective inertial parameter identification method based on sinusoidal vibrations of a six-degree-of-freedom parallel manipulator is proposed. Compared with previously known identification algorithms, the advantages of the new approach are there is no need to design the excitation trajectory to consider the condition number of the observation matrix and the inertial matrix can be accurately defined regardless of the effect of viscous friction. In addition, the use of a sinusoidal exciting trajectory allows calculation of the velocities and accelerations from the measured position response. Simulations show that the new approach has acceptable tolerance of dry friction when using a simple coupling parameter modified formula. The experimental application to the hydraulically driven Stewart platform demonstrates the capability and efficiency of the proposed identification method.展开更多
Recently,frequency-based least-squares(LS)estimators have found wide application in identifying aircraft flutter parameters.However,the frequency methods are often known to suffer from numerical difficulties when iden...Recently,frequency-based least-squares(LS)estimators have found wide application in identifying aircraft flutter parameters.However,the frequency methods are often known to suffer from numerical difficulties when identifying a continuous-time model,especially,of broader frequency or higher order.In this article,a numerically robust LS estimator based on vector orthogonal polynomial is proposed to solve the numerical problem of multivariable systems and applied to the flutter testing.The key idea of this method is to represent the frequency response function(FRF)matrix by a right matrix fraction description(RMFD)model,and expand the numerator and denominator polynomial matrices on a vector orthogonal basis.As a result,a perfect numerical condition(numerical condition equals 1)can be obtained for linear LS estimator.Finally,this method is verified by flutter test of a wing model in a wind tunnel and real flight flutter test of an aircraft.The results are compared to those with notably LMS PolyMAX,which is not troubled by the numerical problem as it is established in z domain(e.g.derived from a discrete-time model).The verification has evidenced that this method,apart from overcoming the numerical problem,yields the results comparable to those acquired with LMS PolyMAX,or even considerably better at some frequency bands.展开更多
文摘In this paper a method of aerodynamic parameter identification of vehicle, the maximum likelihood method, is introduced. The aerodynamic model of vehicle is identified and the basic equations using maximum likelihood method are established. After that, the simulation data is identified to verify the correctness of the mathematic model and identification method. Last, the practical flight data is identified and analyzed.
文摘The identification of aerodynamic parameters is accomplished through the test data of the dynamic movement of scaled aircraft models flying dynamically in wind tunnel,which can real-ize the accurate acquisition of the aerodynamic model of the aircraft in the preliminary stage for aircraft design,and it is of great significance for improving the efficiency of aircraft design.How-ever,the translational motion of the test model in the wind tunnel virtual flight is subject to con-straints that result in distinct flight dynamics compared to free flight.These constraints have implications for the accuracy of aerodynamic derivatives obtained through the identification of wind tunnel test data.With this issue in mind,the research studies the differences in longitudinal dynamic characteristics between unconstrained free flight and wind tunnel virtual flight,and inno-vatively proposes an online correction test based wind tunnel virtual flight test technique.The lon-gitudinal trajectory and velocity changes of the model are solved online by the aerodynamic forces measured during the test,and then the coupled relationship between aircraft translation and rota-tion is used to correct the model's pitch attitude motion online.For the first time,the problem of solving the data approximation for free flight has been solved,eliminating the difference between the dynamics of wind tunnel virtual flight and free flight,and improving the accuracy of the aero-dynamic derivative identification results.The experiment's findings show that accurate aerodynamic derivatives can be identified based on the online correction test data,and the observed behaviour of the identified motion model has similarities to that of the free flight motion model.
基金the National Science and Technology Major Project of China(No.2019-Ⅶ-0017-0158)the National Natural Science Foundation of China(Nos.U2037204,U21A20131)the Innovative Research Team Development Program of Ministry of Education of China(No.IRT17R83)for the support given to this research。
文摘To achieve the manufacturing of Thin-Wall and High-Rib Components(TWHRC)with high precision,a novel heavy load Multi-DOF Envelope Forming Press(MEFP)with Parallel Kinematic Mechanism(PKM),driven by six Permanent Magnet Synchronous Motors(PMSMs),is developed.However,on account of the heavy forming load,the PMSM parameters are in great variation.Meanwhile,the PMSM is always in a transient state caused by fast time-varying forming load,resulting in low identification precision of varied PMSM parameters and control precision of PMSM under traditional parameter identification methods.To solve this problem,a novel Sliding Mode Control Method with Enhanced PMSM Parameter Identification(SMCMEPPI)for heavy load MEFP is proposed.Firstly,the kinematic model of MEFP is established.Secondly,the variation law of PMSM parameters under heavy load is revealed.Thirdly,an enhanced PMSM parameter identification method is proposed,in which the q axis current of PMSM is used to represent the changing rate of forming load and the adjustment factor is first proposed to remove improper input of PMSM parameter identification online.Fourthly,the Electromechanical Coupling Dynamic Model(ECDM)of MEFP,which includes identified PMSM parameters,is developed.Finally,based on the developed ECDM,a novel SMCMEPPI is proposed to realize the high-precision control of heavy load MEFP.The experimental results indicate that the proposed SMCMEPPI can significantly improve the control precision of heavy load MEFP.
文摘A new identification method is proposed to solve the problem of the influence on the loaded excitation signals brought by high feedback gain augmentation in lateral-directional aerodynamic parameters identification of fly-by-wire（FBW） passenger airliners. Taking for example an FBW passenger airliner model with directional relaxed-static-stability, through analysis of its signal energy distribution and airframe frequency response, a new method is proposed for signal type selection, signal parameters design, and the appropriate frequency relationship between the aileron and rudder excitation signals. A simulation validation is presented of the FBW passenger airliner＇s lateral-directional aerodynamic parameters identification. The validation result demonstrates that the designed signal can excite the lateral-directional motion mode of the FBW passenger airliner adequately and persistently. Meanwhile, the relative errors of aerodynamic parameters are less than 5%.
基金supported by the National Natural Science Foundation of China(No.62122083)Youth Innovation Promotion Association,CAS.
文摘In this paper, the problem of time-varying aerodynamic parameters identification under measurement noises is studied. By analyzing the key aerodynamic parameters that affect the aircraft control system, a system model with extended states for identifying equivalent aerodynamic parameters is established, and error parameters are extended to the system state, avoiding the difficulty caused by the unknown dynamic in the system. Furthermore, an identification algorithm based on extended state Kalman filter is designed, and it is proved that the algorithm has quasi-consistency, thus, the estimation error can be evaluated in real time. Finally, the simulation results under typical flight scenarios show that the designed algorithm can accurately identify aerodynamic parameters, and has desired convergence speed and convergence precision.
基金The National Natural Science Foundation of China(No.52338011,52378291)Young Elite Scientists Sponsorship Program by CAST(No.2022-2024QNRC0101).
文摘To overcome the limitations of low efficiency and reliance on manual processes in the measurement of geometric parameters for bridge prefabricated components,a method based on deep learning and computer vision is developed to identify the geometric parameters.The study utilizes a common precast element for highway bridges as the research subject.First,edge feature points of the bridge component section are extracted from images of the precast component cross-sections by combining the Canny operator with mathematical morphology.Subsequently,a deep learning model is developed to identify the geometric parameters of the precast components using the extracted edge coordinates from the images as input and the predefined control parameters of the bridge section as output.A dataset is generated by varying the control parameters and noise levels for model training.Finally,field measurements are conducted to validate the accuracy of the developed method.The results indicate that the developed method effectively identifies the geometric parameters of bridge precast components,with an error rate maintained within 5%.
基金Supported by the National Natural Science Foundation of China(10902051)the Natural Science Foundation of Jiangsu Province(BK2008046)~~
文摘To analyze a multibody system composed of non-uniform beam and spring-mass subsystems, the model discretization is carried on by utilizing the finite element method（FEM）, the dynamic model of non-uniform beam is developed by using the transfer matrix method of multibody system（MS-TMM）, the transfer matrix of non-u- niform beam is derived, and the natural frequencies are computed. Compared with the numerical assembly method （NAM）, the results by MS-TMM have good agreement with the results by FEM, and are better than the results by NAM. When using the high precision method, the global dynamic equations of the complex multibody system are not needed and the orders of involved system matrices are decreased greatly. For the investigation on the re- verse problem of the physical parameter identification of multibody system, MS-TMM and the optimization tech- nology based on genetic algorithms（GAs） are combined and extended. The identification problem is exchanged for an optimization problem, and it is formulated as a global minimum solution of the objective function with respect to natural frequencies of multibody system. At last, the numerical example of non-uniform beam with attach- ments is discussed, and the identification results indicate the feasibility and the effectivity of the proposed aop- proach.
基金supported by the National Natural Science Foundation of China(Grant Nos.62303197,62273214)the Natural Science Foundation of Shandong Province(ZR2024MFO18).
文摘Accurate and reliable photovoltaic(PV)modeling is crucial for the performance evaluation,control,and optimization of PV systems.However,existing methods for PV parameter identification often suffer from limitations in accuracy and efficiency.To address these challenges,we propose an adaptive multi-learning cooperation search algorithm(AMLCSA)for efficient identification of unknown parameters in PV models.AMLCSA is a novel algorithm inspired by teamwork behaviors in modern enterprises.It enhances the original cooperation search algorithm in two key aspects:(i)an adaptive multi-learning strategy that dynamically adjusts search ranges using adaptive weights,allowing better individuals to focus on local exploitation while guiding poorer individuals toward global exploration;and(ii)a chaotic grouping reflection strategy that introduces chaotic sequences to enhance population diversity and improve search performance.The effectiveness of AMLCSA is demonstrated on single-diode,double-diode,and three PV-module models.Simulation results show that AMLCSA offers significant advantages in convergence,accuracy,and stability compared to existing state-of-the-art algorithms.
基金supported by the National Key Research and Development Program of China(No.2023YFC3010400)。
文摘The complex geometrical features of mechanical components significantly influence contact interactions and system dynamics.However,directly modeling contact forces on surfaces with intricate geometries presents considerable challenges.This study focuses on the helically twisted wire rope-sheave contact and proposes a contact force model that incorporates complex geometric features through a parameter identification approach.The model's impact on contact forces and system dynamics is thoroughly investigated.Leveraging a point contact model and an elliptic integral approximation,a loss function is formulated using the finite element(FE)contact model results as the reference data.Geometric parameters are subsequently determined by optimizing this loss function via a genetic algorithm(GA).The findings reveal that the contact stiffness increases with the wire rope pitch length,the radius of principal curvature,and the elliptic eccentricity of the contact zone.The proposed contact force model is integrated into a rigid-flexible coupled dynamics model,developed by the absolute node coordinate formulation,to examine the effects of contact geometry on system dynamics.The results demonstrate that the variations in wire rope geometry alter the contact stiffness,which in turn affects dynamic rope tension through frictional energy dissipation.The enhanced model's predictions exhibit superior alignment with the experimental data,thereby validating the methodology.This approach provides new insights for deducing the contact geometry from kinetic parameters and monitoring the performance degradation of mechanical components.
基金supported by the National Defense Basic Research Program of China(No.B22201320xx)
文摘Abstract This paper describes a longitudinal parameter identification procedure for a small unmanned aerial vehicle （UAV） through modified particle swam optimization （PSO）. The proce- dure is demonstrated using a small UAV equipped with only an micro-electro-mechanical systems （MEMS） inertial mea,mring element and a global positioning system （GPS） receiver to provide test information. A small UAV longitudinal parameter mathematical model is derived and the modified method is proposed based on PSO with selective particle regeneration （SRPSO）. Once modified PSO is applied to the mathematical model, the simulation results show that the mathematical model is correct, and aerodynamic parameters and coefficients of the propeller can be identified accurately. Results are compared with those of PSO and SRPSO and the comparison shows that the proposed method is more robust and faster than the other methods for the longitudinal parameter identification of the small UAV. Some parameter identification results are affected slightly by noise, but the identification results are very good overall. Eventually, experimental validation is employed to test the proposed method, which demonstrates the usefulness of this method.
基金National Natural Science Foundation of China under Grant Nos. 51725901 and 51639006。
文摘Modal parameters, including fundamental frequencies, damping ratios, and mode shapes, could be used to evaluate the health condition of structures. Automatic modal parameter identification, which plays an essential role in realtime structural health monitoring, has become a popular topic in recent years. In this study, an automatic modal parameter identification procedure for high arch dams is proposed. The proposed procedure is implemented by combining the densitybased spatial clustering of applications with noise(DBSCAN) algorithm and the stochastic subspace identification(SSI). The 210-m-high Dagangshan Dam is investigated as an example to verify the feasibility of the procedure. The results show that the DBSCAN algorithm is robust enough to interpret the stabilization diagram from SSI and may avoid outline modes. This leads to the proposed procedure obtaining a better performance than the partitioned clustering and hierarchical clustering algorithms. In addition, the errors of the identified frequencies of the arch dam are within 4%, and the identified mode shapes are in agreement with those obtained from the finite element model, which implies that the proposed procedure is accurate enough to use in modal parameter identification. The procedure is feasible for online modal parameter identification and modal tracking of arch dams.
文摘The flight control system of a fly-by-wire （FBW） passenger airliner with a complex frame-work and high feedback gain augmentation would change the original characteristic of a loaded signal and suppress the excitation of an airplane＇s pertinent motion modes. Taking a research example of an FBW passenger airliner model with longitudinal relaxed-static-stability, a new method of signal type selection and signal parameter design is proposed, through analysis of signal energy distribution and plane body＇s frequency response. According to CCAR60--the Appraisal and Use Regulation of Flight Simulator Device, the simulation validation of the FBW passenger airliner＇s longitudinal aerodynamic parameters identification is put forward. The validation result indicates that the designed signal could excite the longitudinal motion mode of the FBW passenger airliner adequately and the multiparameter comparison in simulation meets the objective test request of CCAR60. Meanwhile, the relative errors of aerodynamic parameters are less than 10%.
文摘Operational Modal Analysis(OMA) refers to the modal analysis of a structure in its operating state. The advantage of OMA is that only the output vibration signal of a system is used in the analysis process. Classic OMA is based on the white noise excitation assumption and many identification methods have been developed in both time domain and frequency domain. But in reality, many environmental excitations are not compliance with the white noise assumption. In this paper, a method of half power bandwidth analysis is applied to power spectrum analysis to deal with the colored noise and trapezoidal spectral excitation. The modal frequencies and modal damping ratios are derived and the error caused by trapezoidal spectral and colored noise excitation are analyzed. It is proved that the OMA algorithm based on the white noise assumption can be extended to the colored noise environments under certain conditions. Finally, a simulation example with a cantilever beam and a vibration test with four kinds of colored noise and trapezoidal spectrum base excitation are carried out and the results support the proposed method.
基金funded by the National Natural Science Foundation of China(Grant No.11172131 and 11232007)the Priority Academic Program Development of Jiangsu Higher Education Institutions。
文摘In this paper,a time–frequency algorithm based on adaptive chirplet transform for parameter modeling and identification of Linear Time-Varying(LTV)systems under random excitation is presented.It is assumed that the solution of responses of LTV structures is expressed as the sum of multicomponent Linear Frequency Modulated(LFM)signals in a short-time.Then the measured acceleration response is used to perform the adaptive chirplet transform,in which an integral algorithm is employed to reconstruct the velocity and displacement responses.The vibration differential equation with time-varying coefficients is transformed into a simple linear equation.Furthermore,for systems under random excitation,the input–output relation based on correlation function is also derived to estimate the parameters including physicals parameters and instantaneous modal parameters.The full procedure of the method is presented and validated by using simulated responses.The results show that the presented method is accurate and robust for various LTV systems under random excitation.
基金financially supported by the Natural Science Foundation of Heilongjiang Province of China (Grant No. LH2020E016)the National Natural Science Foundation of China (Grant No.11472076)。
文摘Offshore platforms are susceptible to structural damage due to prolonged exposure to random loads,such as wind,waves,and currents.This is particularly true for platforms that have been in service for an extended period.Identifying the modal parameters of offshore platforms is crucial for damage diagno sis,as it serves as a prerequisite and foundation for the process.Therefore,it holds great significance to prioritize the identification of these parameters.Aiming at the shortcomings of the traditional Fast Bayesian Fast Fourier Transform(FBFFT) method,this paper proposes a modal parameter identification method based on Automatic Frequency Domain Decomposition(AFDD) and optimized FBFFT.By introducing the AFDD method and Powell optimization algorithm,this method can automatically identify the initial value of natural frequency and solve the objective function efficiently and simply.In order to verify the feasibility and effectiveness of the proposed method,it is used to identify the modal parameters of the IASC-ASCE benchmark model and the j acket platform structure model,and the Most Probable Value(MPV) of the modal parameters and their respective posterior uncertainties are successfully identified.The identification results of the IASC-ASCE benc hmark model are compared with the identification re sults of the MODE-ID method,which verifies the effectivene ss and accuracy of the proposed method for identifying modal parameters.It provides a simple and feasible method for quantifying the influence of uncertain factors such as environmental parameters on the identification results,and also provide s a reference for modal parameter identification of other large structures.
文摘The problem of how to identify the piecewise affine system is studied in this paper, where this considered piecewise affine system is a special nonlinear system. The reason why it is not easy to identify this piecewise affine system is that each separated region and each unknown parameter vector are all needed to be determined simultaneously. Then, firstly, in order to achieve the identification goal, a multi-class classification process is proposed to determine each separated region. As the proposed multi-class classification process is the same with the classical data clustering strategy, the multi-class classification process can combine the first order algorithm of convex optimization, while achieving the goal of the classification process. Secondly, a zonotope parameter identification algorithm is used to construct a set, which contains the unknown parameter vector. In this zonotope parameter identification algorithm, the strict probabilistic description about the external noise is relaxed, and each unknown parameter vector is also identified. Furthermore, this constructed set is consistent with the measured output and the given bound corresponding to the noise. Thirdly, a sufficient condition about guaranteeing our derived zonotope not growing unbounded with iterations is formulated as an explicit linear matrix inequality. Finally, the effectiveness of this zonotope parameter identification algorithm is proven through a simulation example.
基金financial support of the National Natural Science Foundation of China(Nos.52071301,51909238 and 52101333)the Zhejiang Provincial Natural Science Foundation of China(No.LHY21E090001)the Zhejiang Provincial Natural Science Foundation of China(No.LQ21E090009)。
文摘In the actual measurement of offshore wind turbines(OWTs),the measured accelerations usually contain a large amount of noise due to the complex and harsh marine environment,which is not conducive to the identification of structural modal parameters.For OWTs with remarkably low structural modal frequencies,displacements can effectively suppress the high-frequency vibration noise and amplify the low-frequency vibration of the structure.However,finding a reference point to measure structural displacements at sea is difficult.Therefore,only a few studies on the use of dynamic displacements to identify the modal parameters of OWTs with high-pile foundations are available.Hence,this paper develops a displacement conversion strategy to study the modal parameter identification of OWTs with high-pile foundations.The developed strategy can be divided into the following three parts:zero-order correction of measured acceleration,high-pass filtering by the Butterworth polynomial,and modal parameter identification using the calculated displacement.The superiority of the proposed strategy is verified by analyzing a numerical OWT with a high-pile foundation and the measured accelerations from an OWT with a high-pile foundation.The results show that for OWTs with high-pile foundations dominated by low frequencies,the developed strategy of converting accelerations into displacements and then performing modal parameter identification is advantageous to the identification of modal parameters,and the results have high accuracy.
文摘In order to identify aquifer parameter,authors develops an improved combinatorial method called best chromosome clone plus younger generation chromosome prepotency genetic algorithm (BCC-YGCP-GA), based on a decimal system simple genetic algorithm (SGA). The paper takes unsteady state flows in a two dimensional, inhomogeneous, confined aquifer for a ideal model, and utilizes SGA and BCC-YGCP-GA coupled to finite element method for identifying aquifer hydraulic conductivity K 1 ,K 2 ,K 3 and storage S 1 ,S 2 ,S 3 , respectively. It is shown from the result that GSA does not reach convergence with 100 generations, whereas convergence rate of BCC-YGCD-GA is very fast. Objective function value calculated by BCC-YGCD-GA is 0 001 29 with 100 generations, and hydraulic conductivity and storage of three zones are almost equal to the "true" values of ideal model.
基金financially supported by the National Natural Science Foundation of China (No. 50975055)
文摘A new simple and effective inertial parameter identification method based on sinusoidal vibrations of a six-degree-of-freedom parallel manipulator is proposed. Compared with previously known identification algorithms, the advantages of the new approach are there is no need to design the excitation trajectory to consider the condition number of the observation matrix and the inertial matrix can be accurately defined regardless of the effect of viscous friction. In addition, the use of a sinusoidal exciting trajectory allows calculation of the velocities and accelerations from the measured position response. Simulations show that the new approach has acceptable tolerance of dry friction when using a simple coupling parameter modified formula. The experimental application to the hydraulically driven Stewart platform demonstrates the capability and efficiency of the proposed identification method.
基金Aeronautical Science Foundation of China(2007ZD53053)NPU Foundation for Fundamental Research(NPU-FFR-W018104)
文摘Recently,frequency-based least-squares(LS)estimators have found wide application in identifying aircraft flutter parameters.However,the frequency methods are often known to suffer from numerical difficulties when identifying a continuous-time model,especially,of broader frequency or higher order.In this article,a numerically robust LS estimator based on vector orthogonal polynomial is proposed to solve the numerical problem of multivariable systems and applied to the flutter testing.The key idea of this method is to represent the frequency response function(FRF)matrix by a right matrix fraction description(RMFD)model,and expand the numerator and denominator polynomial matrices on a vector orthogonal basis.As a result,a perfect numerical condition(numerical condition equals 1)can be obtained for linear LS estimator.Finally,this method is verified by flutter test of a wing model in a wind tunnel and real flight flutter test of an aircraft.The results are compared to those with notably LMS PolyMAX,which is not troubled by the numerical problem as it is established in z domain(e.g.derived from a discrete-time model).The verification has evidenced that this method,apart from overcoming the numerical problem,yields the results comparable to those acquired with LMS PolyMAX,or even considerably better at some frequency bands.
