In complex systems,there is a kind of parameters having only a minor impact on the outputs in most cases,but their accurate values are still critical for the operation of systems.In this paper,the authors focus on the...In complex systems,there is a kind of parameters having only a minor impact on the outputs in most cases,but their accurate values are still critical for the operation of systems.In this paper,the authors focus on the identification of these weak influence parameters in the complex systems and propose a identification model based on the parameter recursion.As an application,three parameters of the steam generator are identified,that is,the valve opening,the valve CV value,and the reference water level,in which the valve opening and the reference water level are weak influence parameters under most operating conditions.Numerical simulation results show that,in comparison with the multi-layer perceptron(MLP),the identification error rate is decreased.Actually,the average identification error rate for the valve opening decreases by 0.96%,for the valve CV decreases by 0.002%,and for the reference water level decreases by 12%after one recursion.After two recursions,the average identification error rate for the valve opening decreases by 11.07%,for the valve CV decreases by 2.601%,and for the reference water level decreases by 95.79%.This method can help to improve the control of the steam generator.展开更多
Accurate identification of unknown internal parameters in photovoltaic(PV)cells is crucial and significantly affects the subsequent system-performance analysis and control.However,noise,insufficient data acquisition,a...Accurate identification of unknown internal parameters in photovoltaic(PV)cells is crucial and significantly affects the subsequent system-performance analysis and control.However,noise,insufficient data acquisition,and loss of recorded data can deteriorate the extraction accuracy of unknown parameters.Hence,this study proposes an intelligent parameter-identification strategy that integrates artificial ecosystem optimization(AEO)and a Bayesian neural network(BNN)for PV cell parameter extraction.A BNN is used for data preprocessing,including data denoising and prediction.Furthermore,the AEO algorithm is utilized to identify unknown parameters in the single-diode model(SDM),double-diode model(DDM),and three-diode model(TDM).Nine other metaheuristic algorithms(MhAs)are adopted for an unbiased and comprehensive validation.Simulation results show that BNN-based data preprocessing com-bined with effective MhAs significantly improve the parameter-extraction accuracy and stability compared with methods without data preprocessing.For instance,under denoised data,the accuracies of the SDM,DDM,and TDM increase by 99.69%,99.70%,and 99.69%,respectively,whereas their accuracy improvements increase by 66.71%,59.65%,and 70.36%,respectively.展开更多
In view of the feature of flight flutter test data with atmospheric turbulence excitation, a method which combines wavelet transformation with random decrement technique for identifying flight flutter modal parameters...In view of the feature of flight flutter test data with atmospheric turbulence excitation, a method which combines wavelet transformation with random decrement technique for identifying flight flutter modal parameters is presented. This approach firstly uses random decrement technique to gain free decays corresponding to the acceleration response of the structure to some non-zero initial conditions. Then the continuous Morlet wavelet transformation of the free decays is performed; and the Parseval formula and residue theorem are used to simplify the transformation. The maximal wavelet transformation coefficients in different scales are searched out by means of band-filtering characteristic of Morlet wavelet, and then the modal parameters are identified according to the relationships with maximal modulus and angle of the wavelet transform. In addition, the condition of modal uncoupling is discussed according to variation trend of flight flutter modal parameters in the flight flutter state. The analysis results of simulation and flight flutter test data show that this approach is not only simple, effective and feasible, but also having good noise immunity.展开更多
To accurately describe the mechanical properties of aluminium alloy sheet during deformation, an inverse identification was presented to deal with material parameters from the popular punch stretch test. In the identi...To accurately describe the mechanical properties of aluminium alloy sheet during deformation, an inverse identification was presented to deal with material parameters from the popular punch stretch test. In the identification procedure, the optimization strategy combines finite element method （FEM）, Latin hypercube sampling （LHS）, Kriging model and multi-island genetic algorithm （MIGA）. The proposed approach is used on material parameter identification of aluminium alloy sheet 2D12. The anisotropic yield criterion Hill’90 is discussed. The results show that the Hill’90 anisotropic yield criterion with identified anisotropic material parameters has a good potential in describing the anisotropic behaviours. It provides a way to obtain the material parameters for FE simulations of sheet metal forming.展开更多
The vibration caused blade High Cycle Fatigue(HCF)is seriously affects the safety operation of turbomachinery especially for aero-engine.Thus,it is crucial important to identify the blade vibration parameters and then...The vibration caused blade High Cycle Fatigue(HCF)is seriously affects the safety operation of turbomachinery especially for aero-engine.Thus,it is crucial important to identify the blade vibration parameters and then evaluate the dynamic stress amplitude.Blade Tip Timing(BTT)method is one of the promising method to solve these problems.While,it need a high resolution Once Per Revolution(OPR)signal which is difficult to get for the aero-engine.Here,a Coupled Vibration Analysis(CVA)method for identifying blade vibration parameters by a none OPR BTT is proposed.The method assumes that every real blade has its own vibration performance at a given speed.Whereby,it can take any blade as the reference blade,and the other blades using the reference blade as the OPR for vibration displacement calculating and further parameter identifying.The proposed method is validated by numerical model.Also,experimental studies are carried out on a straight blade and a twisted three dimensional blade test rig as well as a large industrial axial compressor respectively.The results show that the proposed method can accurately identify the blade synchronous vibration parameters and quantitatively evaluate the mistuning in bladed disks,which lays a foundation for the reliability improvement of aero-engine.展开更多
The inverse heat conduction method is one of methods to identify the casting simulation parameters. A new inverse method was presented according to the Tikhonov regularization theory. One appropriate regularized funct...The inverse heat conduction method is one of methods to identify the casting simulation parameters. A new inverse method was presented according to the Tikhonov regularization theory. One appropriate regularized functional was established, and the functional was solved by the sensitivity coefficient and Newtonaphson iteration method. Moreover, the orthogonal experimental design was used to estimate the appropriate initial value and variation domain of each variable to decrease the number of iteration and improve the identification accuracy and efficiency. It illustrated a detailed case of AlSiTMg sand mold casting and the temperature measurement experiment was done. The physical properties of sand mold and the interracial heat transfer coefficient were identified at the meantime. The results indicated that the new regularization method was efficient in overcoming the ill-posedness of the inverse heat conduction problem and improving the stability and accuracy of the solutions.展开更多
Nuclear power plants(NPP)contain plenty of valve piping systems(VPS’s)which are categorized into high anti-seismic grades.Tasks such as seismic qualification,health monitoring and damage diagnosis of VPS’s in its de...Nuclear power plants(NPP)contain plenty of valve piping systems(VPS’s)which are categorized into high anti-seismic grades.Tasks such as seismic qualification,health monitoring and damage diagnosis of VPS’s in its design and operation processes all depend on finite element method.However,in engineering practice,there is always deviations between the theoretical and the measured responses due to the inaccurate value of the structural parameters in the model.The structure parameters identification of VPS within NPP is still an unexplored domain to a large extent.In this paper,the initial 2D-finite element model(FEM)for VPS with a DN80 gate valve was updated by utilizing seismic response.The objective function used in the model updating procedure is the vibration control equation error of the VPS.The experimental results show that the updated 2D-FEM can accurately predict the original dynamic characteristic of the VPS.It was also found the Rayleigh damping coefficients corresponding to the VPS vary slightly with the change in seismic excitation amplitude.The research displayed the complete procedure of updating the complex structured initial FEM by utilizing seismic response,and the results show that the parameters can be accurately identified even if the seismic response used for updating merely contained the fundamental frequency information of the structure.展开更多
A new method of parameter identification based on linear time-frequencyrepresentation and Hubert transform is proposed to identity modal parameters of linear time-varyingsystems from measured vibration responses. Usin...A new method of parameter identification based on linear time-frequencyrepresentation and Hubert transform is proposed to identity modal parameters of linear time-varyingsystems from measured vibration responses. Using Gabor expansion and synthesis theory, measuredresponses are represented in the time-frequency domain and modal components are reconstructed bytime-frequency filtering. The Hilbert transform is applied to obtain time histories of the amplitudeand phase angle of each modal component, from which time-varying frequencies and damping ratios areidentified. The proposed method has been demonstrated with a numerical example in which a lineartime-varying system of two degrees of freedom is used to validate the identification scheme based ontime-frequency representation. Simulation results have indicated that time-frequency representationpresents an effective tool for modal parameter identification of time-varying systems.展开更多
Joint parameter identification is a key problem in the modeling of complex structures. The behavior of joint may be random due to the random properties of preload and joint geometries, contact surface and its finish, ...Joint parameter identification is a key problem in the modeling of complex structures. The behavior of joint may be random due to the random properties of preload and joint geometries, contact surface and its finish, etc. A method is presented to simulate the joint parameters as probabilistic variables. In this method the response surface based model updating method and probabilistic approaches are employed to identify the parameters. The study implies that joint parameters of some structures have normal or nearly normal distributions, and a linear FE model with probabilistic variables could illustrate dynamic characteristics of joints.展开更多
Parameter identification is a key requirement in the field of automated control of unmanned excavators （UEs）. Furthermore, the UE operates in unstructured, often hazardous environments, and requires a robust paramet...Parameter identification is a key requirement in the field of automated control of unmanned excavators （UEs）. Furthermore, the UE operates in unstructured, often hazardous environments, and requires a robust parameter identification scheme for field applications. This paper presents the results of a research study on parameter identification for UE. Three identification methods, the Newton-Raphson method, the generalized Newton method, and the least squares method are used and compared for prediction accuracy, robustness to noise and computational speed. The techniques are used to identify the link parameters （mass, inertia, and length） and friction coefficients of the full-scale UE. Using experimental data from a full-scale field UE, the values of link parameters and the friction coefficient are identified. Some of the identified parameters are compared with measured physical values. Furthermore, the joint torques and positions computed by the proposed model using the identified parameters are validated against measured data. The comparison shows that both the Newton-Raphson method and the generalized Newton method are better in terms of prediction accuracy. The Newton-Raphson method is computationally efficient and has potential for real time application, but the generalized Newton method is slightly more robust to measurement noise. The experimental data were obtained in collaboration with QinetiQ Ltd.展开更多
A hybrid numerical-experimental approach to identify elastic modulus of a textile composite panel using vibration test data is proposed and investi- gated. Homogenization method is adopted to predict the initial value...A hybrid numerical-experimental approach to identify elastic modulus of a textile composite panel using vibration test data is proposed and investi- gated. Homogenization method is adopted to predict the initial values of elastic parameters of the composite, and parameter identification is transformed to an optimization problem in which the objective function is the minimization of the discrepancies between the experimental and numerical modal data. Case study is conducted employing a woven fabric reinforced composite panel. Three parameters （Ell, E22, G12） with higher sensitivities are selected to be identified. It is shown that the elastic parameters can be accurately identified from experimental modal data.展开更多
An electrical equivalent circuit model for lithium-ion batteries used for hybrid electric vehicles （HEV） is presented. The model has two RC networks characterizing battery activation and concentration polarization p...An electrical equivalent circuit model for lithium-ion batteries used for hybrid electric vehicles （HEV） is presented. The model has two RC networks characterizing battery activation and concentration polarization process. The parameters of the model are identified using combined experimental and extended Kalman filter （EKF） recursive methods. The open-circuit voltage and ohmic resistance of the battery are directly measured and calculated from experimental measurements, respectively. The rest of the coupled dynamic parameters, i.e. the RC network parameters, are estimated using the EKF method. Experimental and simulation results are presented to demonstrate the efficacy of the proposed circuit model and parameter identification techniques for simulating battery dynamics.展开更多
Empirical mode decomposition (EMD) is proposed to identify linear structure under non-stationary excitation,and non-white noise coefficient is introduced under the assumption of random signals consisting of white nois...Empirical mode decomposition (EMD) is proposed to identify linear structure under non-stationary excitation,and non-white noise coefficient is introduced under the assumption of random signals consisting of white noise and non-white noise signals. The cross-correlation function of response signal is decomposed into mode functions and residue by EMD method. The identification technique of the modal parameters of single freedom degree is applied to each mode function to obtain natural frequencies, damping ratios and mode shapes. The results of identification of the five-degree freedom linear system demonstrate that the proposed method is effective in identifying the parameters of linear structures under non-stationary ambient excitation.展开更多
In this paper, we propose a general method to simultaneously identify both unknown time delays and unknown model parameters in delayed dynamical systems based on the autosynchronization technique. The design procedure...In this paper, we propose a general method to simultaneously identify both unknown time delays and unknown model parameters in delayed dynamical systems based on the autosynchronization technique. The design procedure is presented in detail by constructing a specific Lyapunov function and linearizing the model function with nonlinear parameterization. The obtained result can be directly extended to the identification problem of linearly parameterized dynamical systems. Two Wpical numerical examples confirming the effectiveness of the identification method are given.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
A time-varying modal parameter identification method combined with Bayesian information criterion(BIC)and grey correlation analysis(GCA)is presented for a kind of thermo-elastic structures with sparse natural frequenc...A time-varying modal parameter identification method combined with Bayesian information criterion(BIC)and grey correlation analysis(GCA)is presented for a kind of thermo-elastic structures with sparse natural frequencies and subject to an unsteady temperature field.To demonstrate the method,the thermo-elastic structure to be identified is taken as a simply-supported beam with an axially movable boundary and subject to both random excitation and an unsteady temperature field,and the dynamic outputs of the beam are first simulated as the measured data for the identification.Then,an improved time-varying autoregressive(TVAR)model is generated from the simulated input and output of the system.The time-varying coefficients of the TVAR model are expanded as a finite set of time basis functions that facilitate the time-varying coefficients to be time-invariant.According to the BIC for preliminarily determining the scope of the order number,the grey system theory is introduced to determine the order of TVAR and the dimension of the basis functions simultaneously via the absolute grey correlation degree(AGCD).Finally,the time-varying instantaneous frequencies of the system are estimated by using the recursive least squares method.The identified results are capable of tracking the slow time-varying natural frequencies with high accuracy no matter for noise-free or noisy estimation.展开更多
Exoskeletons generally require accurate dynamic models to design the model-based controller conveniently under the human-robot interaction condition.However,due to unknown model parameters such as the mass,moment of i...Exoskeletons generally require accurate dynamic models to design the model-based controller conveniently under the human-robot interaction condition.However,due to unknown model parameters such as the mass,moment of inertia and mechanical size,the dynamic model of exoskeletons is difficult to construct.Hence,an enhanced whale optimization algorithm(EWOA)is proposed to identify the exoskeleton model parameters.Meanwhile,the periodic excitation trajectories are designed by finite Fourier series to input the desired position demand of exoskeletons with mechanical physical constraints.Then a backstepping controller based on the identified model is adopted to improve the human-robot wearable comfortable performance under cooperative motion.Finally,the proposed Model parameters identification and control are verified by a two-DOF exoskeletons platform.The knee joint motion achieves a steady-state response after 0.5 s.Meanwhile,the position error of hip joint response is less than 0.03 rad after 0.9 s.In addition,the steady-state human-robot interaction torque of the two joints is constrained within 15 N·m.This research proposes a whale optimization algorithm to optimize the excitation trajectory and identify model parameters.Furthermore,an enhanced mutation strategy is adopted to avoid whale evolution’s unsatisfactory local optimal value.展开更多
Due to the geological body uncertainty,the identification of the surrounding rock parameters in the tunnel construction process is of great significance to the calculation of tunnel stability.The ubiquitous-joint mode...Due to the geological body uncertainty,the identification of the surrounding rock parameters in the tunnel construction process is of great significance to the calculation of tunnel stability.The ubiquitous-joint model and three-dimensional numerical simulation have advantages in the parameter identification of surrounding rock with weak planes,but conventional methods have certain problems,such as a large number of parameters and large time consumption.To solve the problems,this study combines the orthogonal design,Gaussian process(GP)regression,and difference evolution(DE)optimization,and it constructs the parameters identification method of the jointed surrounding rock.The calculation process of parameters identification of a tunnel jointed surrounding rock based on the GP optimized by the DE includes the following steps.First,a three-dimensional numerical simulation based on the ubiquitous-joint model is conducted according to the orthogonal and uniform design parameters combing schemes,where the model input consists of jointed rock parameters and model output is the information on the surrounding rock displacement and stress.Then,the GP regress model optimized by DE is trained by the data samples.Finally,the GP model is integrated into the DE algorithm,and the absolute differences in the displacement and stress between calculated and monitored values are used as the objective function,while the parameters of the jointed surrounding rock are used as variables and identified.The proposed method is verified by the experiments with a joint rock surface in the Dadongshan tunnel,which is located in Dalian,China.The obtained calculation and analysis results are as follows:CR=0.9,F=0.6,NP=100,and the difference strategy DE/Best/1 is recommended.The results of the back analysis are compared with the field monitored values,and the relative error is 4.58%,which is satisfactory.The algorithm influencing factors are also discussed,and it is found that the local correlation coefficientσf and noise standard deviationσn affected the prediction accuracy of the GP model.The results show that the proposed method is feasible and can achieve high identification precision.The study provides an effective reference for parameter identification of jointed surrounding rock in a tunnel.展开更多
This study presented an off-line identification method of induction motor (IM) parameters. Before startup,the inverter drive performed automatically a modified DC test, a locked-rotor test, a no-load test and a step-v...This study presented an off-line identification method of induction motor (IM) parameters. Before startup,the inverter drive performed automatically a modified DC test, a locked-rotor test, a no-load test and a step-voltage test to identify all the parameters of an induction motor. No manual operation and speed signals were required in the process. In order to obtain effective messages and improve the accuracy of identification, the discrete fast Fourier transform (DFFT) and the least-squares were used to process the signals of currents and voltages. A phase-voltage measuring method for motors was also proposed, which measured directly the actual conducting time of three upper switches in the inverter without need for a dead-time compensator. The validity, reliability and accuracy of the presented methods have been verified by the experiments on a VSI-fed IM drive system.展开更多
Based on Lyapunov stability theory, a novel adaptive controller is designed for a class of chaotic systems .The parameters identification and synchronization of chaotic systems can be carried out simultaneously. The c...Based on Lyapunov stability theory, a novel adaptive controller is designed for a class of chaotic systems .The parameters identification and synchronization of chaotic systems can be carried out simultaneously. The controller and the updating law of parameters identification are directly constructed by analytic formula. Simulation results with Chen’s system and R?ssler system show the effectiveness of the proposed controller.展开更多
文摘In complex systems,there is a kind of parameters having only a minor impact on the outputs in most cases,but their accurate values are still critical for the operation of systems.In this paper,the authors focus on the identification of these weak influence parameters in the complex systems and propose a identification model based on the parameter recursion.As an application,three parameters of the steam generator are identified,that is,the valve opening,the valve CV value,and the reference water level,in which the valve opening and the reference water level are weak influence parameters under most operating conditions.Numerical simulation results show that,in comparison with the multi-layer perceptron(MLP),the identification error rate is decreased.Actually,the average identification error rate for the valve opening decreases by 0.96%,for the valve CV decreases by 0.002%,and for the reference water level decreases by 12%after one recursion.After two recursions,the average identification error rate for the valve opening decreases by 11.07%,for the valve CV decreases by 2.601%,and for the reference water level decreases by 95.79%.This method can help to improve the control of the steam generator.
基金supported by the National Natural Science Foundation of China(62263014)the Yunnan Provincial Basic Research Project(202301AT070443,202401AT070344).
文摘Accurate identification of unknown internal parameters in photovoltaic(PV)cells is crucial and significantly affects the subsequent system-performance analysis and control.However,noise,insufficient data acquisition,and loss of recorded data can deteriorate the extraction accuracy of unknown parameters.Hence,this study proposes an intelligent parameter-identification strategy that integrates artificial ecosystem optimization(AEO)and a Bayesian neural network(BNN)for PV cell parameter extraction.A BNN is used for data preprocessing,including data denoising and prediction.Furthermore,the AEO algorithm is utilized to identify unknown parameters in the single-diode model(SDM),double-diode model(DDM),and three-diode model(TDM).Nine other metaheuristic algorithms(MhAs)are adopted for an unbiased and comprehensive validation.Simulation results show that BNN-based data preprocessing com-bined with effective MhAs significantly improve the parameter-extraction accuracy and stability compared with methods without data preprocessing.For instance,under denoised data,the accuracies of the SDM,DDM,and TDM increase by 99.69%,99.70%,and 99.69%,respectively,whereas their accuracy improvements increase by 66.71%,59.65%,and 70.36%,respectively.
基金National Natural Science Foundation of China(60134010)
文摘In view of the feature of flight flutter test data with atmospheric turbulence excitation, a method which combines wavelet transformation with random decrement technique for identifying flight flutter modal parameters is presented. This approach firstly uses random decrement technique to gain free decays corresponding to the acceleration response of the structure to some non-zero initial conditions. Then the continuous Morlet wavelet transformation of the free decays is performed; and the Parseval formula and residue theorem are used to simplify the transformation. The maximal wavelet transformation coefficients in different scales are searched out by means of band-filtering characteristic of Morlet wavelet, and then the modal parameters are identified according to the relationships with maximal modulus and angle of the wavelet transform. In addition, the condition of modal uncoupling is discussed according to variation trend of flight flutter modal parameters in the flight flutter state. The analysis results of simulation and flight flutter test data show that this approach is not only simple, effective and feasible, but also having good noise immunity.
基金Project(2011YSKF01)supported by the Henan Key Laboratory of Advanced Non-ferrous Metals,ChinaProject(50905008)supported by the National Natural Science Foundation of China
文摘To accurately describe the mechanical properties of aluminium alloy sheet during deformation, an inverse identification was presented to deal with material parameters from the popular punch stretch test. In the identification procedure, the optimization strategy combines finite element method （FEM）, Latin hypercube sampling （LHS）, Kriging model and multi-island genetic algorithm （MIGA）. The proposed approach is used on material parameter identification of aluminium alloy sheet 2D12. The anisotropic yield criterion Hill’90 is discussed. The results show that the Hill’90 anisotropic yield criterion with identified anisotropic material parameters has a good potential in describing the anisotropic behaviours. It provides a way to obtain the material parameters for FE simulations of sheet metal forming.
基金supported financially by Natural Science Foundation of China(Nos.51775030,91860126)the Fundamental Research Funds for the Central Universities(No.BHYC1703A)。
文摘The vibration caused blade High Cycle Fatigue(HCF)is seriously affects the safety operation of turbomachinery especially for aero-engine.Thus,it is crucial important to identify the blade vibration parameters and then evaluate the dynamic stress amplitude.Blade Tip Timing(BTT)method is one of the promising method to solve these problems.While,it need a high resolution Once Per Revolution(OPR)signal which is difficult to get for the aero-engine.Here,a Coupled Vibration Analysis(CVA)method for identifying blade vibration parameters by a none OPR BTT is proposed.The method assumes that every real blade has its own vibration performance at a given speed.Whereby,it can take any blade as the reference blade,and the other blades using the reference blade as the OPR for vibration displacement calculating and further parameter identifying.The proposed method is validated by numerical model.Also,experimental studies are carried out on a straight blade and a twisted three dimensional blade test rig as well as a large industrial axial compressor respectively.The results show that the proposed method can accurately identify the blade synchronous vibration parameters and quantitatively evaluate the mistuning in bladed disks,which lays a foundation for the reliability improvement of aero-engine.
文摘The inverse heat conduction method is one of methods to identify the casting simulation parameters. A new inverse method was presented according to the Tikhonov regularization theory. One appropriate regularized functional was established, and the functional was solved by the sensitivity coefficient and Newtonaphson iteration method. Moreover, the orthogonal experimental design was used to estimate the appropriate initial value and variation domain of each variable to decrease the number of iteration and improve the identification accuracy and efficiency. It illustrated a detailed case of AlSiTMg sand mold casting and the temperature measurement experiment was done. The physical properties of sand mold and the interracial heat transfer coefficient were identified at the meantime. The results indicated that the new regularization method was efficient in overcoming the ill-posedness of the inverse heat conduction problem and improving the stability and accuracy of the solutions.
文摘Nuclear power plants(NPP)contain plenty of valve piping systems(VPS’s)which are categorized into high anti-seismic grades.Tasks such as seismic qualification,health monitoring and damage diagnosis of VPS’s in its design and operation processes all depend on finite element method.However,in engineering practice,there is always deviations between the theoretical and the measured responses due to the inaccurate value of the structural parameters in the model.The structure parameters identification of VPS within NPP is still an unexplored domain to a large extent.In this paper,the initial 2D-finite element model(FEM)for VPS with a DN80 gate valve was updated by utilizing seismic response.The objective function used in the model updating procedure is the vibration control equation error of the VPS.The experimental results show that the updated 2D-FEM can accurately predict the original dynamic characteristic of the VPS.It was also found the Rayleigh damping coefficients corresponding to the VPS vary slightly with the change in seismic excitation amplitude.The research displayed the complete procedure of updating the complex structured initial FEM by utilizing seismic response,and the results show that the parameters can be accurately identified even if the seismic response used for updating merely contained the fundamental frequency information of the structure.
基金Automobile Industrial Science Foundation of Shanghai (No.2000187)
文摘A new method of parameter identification based on linear time-frequencyrepresentation and Hubert transform is proposed to identity modal parameters of linear time-varyingsystems from measured vibration responses. Using Gabor expansion and synthesis theory, measuredresponses are represented in the time-frequency domain and modal components are reconstructed bytime-frequency filtering. The Hilbert transform is applied to obtain time histories of the amplitudeand phase angle of each modal component, from which time-varying frequencies and damping ratios areidentified. The proposed method has been demonstrated with a numerical example in which a lineartime-varying system of two degrees of freedom is used to validate the identification scheme based ontime-frequency representation. Simulation results have indicated that time-frequency representationpresents an effective tool for modal parameter identification of time-varying systems.
文摘Joint parameter identification is a key problem in the modeling of complex structures. The behavior of joint may be random due to the random properties of preload and joint geometries, contact surface and its finish, etc. A method is presented to simulate the joint parameters as probabilistic variables. In this method the response surface based model updating method and probabilistic approaches are employed to identify the parameters. The study implies that joint parameters of some structures have normal or nearly normal distributions, and a linear FE model with probabilistic variables could illustrate dynamic characteristics of joints.
基金This work was supported by the EPSRC(No.GR/R50738/01).
文摘Parameter identification is a key requirement in the field of automated control of unmanned excavators （UEs）. Furthermore, the UE operates in unstructured, often hazardous environments, and requires a robust parameter identification scheme for field applications. This paper presents the results of a research study on parameter identification for UE. Three identification methods, the Newton-Raphson method, the generalized Newton method, and the least squares method are used and compared for prediction accuracy, robustness to noise and computational speed. The techniques are used to identify the link parameters （mass, inertia, and length） and friction coefficients of the full-scale UE. Using experimental data from a full-scale field UE, the values of link parameters and the friction coefficient are identified. Some of the identified parameters are compared with measured physical values. Furthermore, the joint torques and positions computed by the proposed model using the identified parameters are validated against measured data. The comparison shows that both the Newton-Raphson method and the generalized Newton method are better in terms of prediction accuracy. The Newton-Raphson method is computationally efficient and has potential for real time application, but the generalized Newton method is slightly more robust to measurement noise. The experimental data were obtained in collaboration with QinetiQ Ltd.
基金supported by the Program for New Century Excellent Talents in University(NCET11-0086)the National Natural Science Foundation of China(10902024)+1 种基金the Doctoral Program of Higher Education of China(20130092120039)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD-1105007001)
文摘A hybrid numerical-experimental approach to identify elastic modulus of a textile composite panel using vibration test data is proposed and investi- gated. Homogenization method is adopted to predict the initial values of elastic parameters of the composite, and parameter identification is transformed to an optimization problem in which the objective function is the minimization of the discrepancies between the experimental and numerical modal data. Case study is conducted employing a woven fabric reinforced composite panel. Three parameters （Ell, E22, G12） with higher sensitivities are selected to be identified. It is shown that the elastic parameters can be accurately identified from experimental modal data.
文摘An electrical equivalent circuit model for lithium-ion batteries used for hybrid electric vehicles （HEV） is presented. The model has two RC networks characterizing battery activation and concentration polarization process. The parameters of the model are identified using combined experimental and extended Kalman filter （EKF） recursive methods. The open-circuit voltage and ohmic resistance of the battery are directly measured and calculated from experimental measurements, respectively. The rest of the coupled dynamic parameters, i.e. the RC network parameters, are estimated using the EKF method. Experimental and simulation results are presented to demonstrate the efficacy of the proposed circuit model and parameter identification techniques for simulating battery dynamics.
基金National Natural Science Foundation(No.19972016)for partly supporting this work
文摘Empirical mode decomposition (EMD) is proposed to identify linear structure under non-stationary excitation,and non-white noise coefficient is introduced under the assumption of random signals consisting of white noise and non-white noise signals. The cross-correlation function of response signal is decomposed into mode functions and residue by EMD method. The identification technique of the modal parameters of single freedom degree is applied to each mode function to obtain natural frequencies, damping ratios and mode shapes. The results of identification of the five-degree freedom linear system demonstrate that the proposed method is effective in identifying the parameters of linear structures under non-stationary ambient excitation.
基金supported by the National Science and Technology Major Project of the Ministry of Science and Technology of China (Grant No. 2011ZX03005-002)the Shandong Academy of Science Development Fund for Science and Technology, Chinathe Pilot Project for Science and Technology in Shandong Academy of Science, China
文摘In this paper, we propose a general method to simultaneously identify both unknown time delays and unknown model parameters in delayed dynamical systems based on the autosynchronization technique. The design procedure is presented in detail by constructing a specific Lyapunov function and linearizing the model function with nonlinear parameterization. The obtained result can be directly extended to the identification problem of linearly parameterized dynamical systems. Two Wpical numerical examples confirming the effectiveness of the identification method are given.
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Supported by the National Natural Science Foundation of China(91216103)the Funding of Jiangsu Innovation Program for Graduate Education(CXLX13_130)+1 种基金the Fundamental Research Funds for the Central Universitiesthe Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘A time-varying modal parameter identification method combined with Bayesian information criterion(BIC)and grey correlation analysis(GCA)is presented for a kind of thermo-elastic structures with sparse natural frequencies and subject to an unsteady temperature field.To demonstrate the method,the thermo-elastic structure to be identified is taken as a simply-supported beam with an axially movable boundary and subject to both random excitation and an unsteady temperature field,and the dynamic outputs of the beam are first simulated as the measured data for the identification.Then,an improved time-varying autoregressive(TVAR)model is generated from the simulated input and output of the system.The time-varying coefficients of the TVAR model are expanded as a finite set of time basis functions that facilitate the time-varying coefficients to be time-invariant.According to the BIC for preliminarily determining the scope of the order number,the grey system theory is introduced to determine the order of TVAR and the dimension of the basis functions simultaneously via the absolute grey correlation degree(AGCD).Finally,the time-varying instantaneous frequencies of the system are estimated by using the recursive least squares method.The identified results are capable of tracking the slow time-varying natural frequencies with high accuracy no matter for noise-free or noisy estimation.
基金Supported by National Key Research and Development Program of China(Grant No.2022YFF0708903)Ningbo Municipal Key Technology Research and Development Program of China(Grant No.2022Z006)Youth Fund of National Natural Science Foundation of China(Grant No.52205043)。
文摘Exoskeletons generally require accurate dynamic models to design the model-based controller conveniently under the human-robot interaction condition.However,due to unknown model parameters such as the mass,moment of inertia and mechanical size,the dynamic model of exoskeletons is difficult to construct.Hence,an enhanced whale optimization algorithm(EWOA)is proposed to identify the exoskeleton model parameters.Meanwhile,the periodic excitation trajectories are designed by finite Fourier series to input the desired position demand of exoskeletons with mechanical physical constraints.Then a backstepping controller based on the identified model is adopted to improve the human-robot wearable comfortable performance under cooperative motion.Finally,the proposed Model parameters identification and control are verified by a two-DOF exoskeletons platform.The knee joint motion achieves a steady-state response after 0.5 s.Meanwhile,the position error of hip joint response is less than 0.03 rad after 0.9 s.In addition,the steady-state human-robot interaction torque of the two joints is constrained within 15 N·m.This research proposes a whale optimization algorithm to optimize the excitation trajectory and identify model parameters.Furthermore,an enhanced mutation strategy is adopted to avoid whale evolution’s unsatisfactory local optimal value.
基金This work was supported by the National Natural Science Foundation of China(Nos.51678101,52078093)Liaoning Revitalization Talents Program(No.XLYC1905015).
文摘Due to the geological body uncertainty,the identification of the surrounding rock parameters in the tunnel construction process is of great significance to the calculation of tunnel stability.The ubiquitous-joint model and three-dimensional numerical simulation have advantages in the parameter identification of surrounding rock with weak planes,but conventional methods have certain problems,such as a large number of parameters and large time consumption.To solve the problems,this study combines the orthogonal design,Gaussian process(GP)regression,and difference evolution(DE)optimization,and it constructs the parameters identification method of the jointed surrounding rock.The calculation process of parameters identification of a tunnel jointed surrounding rock based on the GP optimized by the DE includes the following steps.First,a three-dimensional numerical simulation based on the ubiquitous-joint model is conducted according to the orthogonal and uniform design parameters combing schemes,where the model input consists of jointed rock parameters and model output is the information on the surrounding rock displacement and stress.Then,the GP regress model optimized by DE is trained by the data samples.Finally,the GP model is integrated into the DE algorithm,and the absolute differences in the displacement and stress between calculated and monitored values are used as the objective function,while the parameters of the jointed surrounding rock are used as variables and identified.The proposed method is verified by the experiments with a joint rock surface in the Dadongshan tunnel,which is located in Dalian,China.The obtained calculation and analysis results are as follows:CR=0.9,F=0.6,NP=100,and the difference strategy DE/Best/1 is recommended.The results of the back analysis are compared with the field monitored values,and the relative error is 4.58%,which is satisfactory.The algorithm influencing factors are also discussed,and it is found that the local correlation coefficientσf and noise standard deviationσn affected the prediction accuracy of the GP model.The results show that the proposed method is feasible and can achieve high identification precision.The study provides an effective reference for parameter identification of jointed surrounding rock in a tunnel.
文摘This study presented an off-line identification method of induction motor (IM) parameters. Before startup,the inverter drive performed automatically a modified DC test, a locked-rotor test, a no-load test and a step-voltage test to identify all the parameters of an induction motor. No manual operation and speed signals were required in the process. In order to obtain effective messages and improve the accuracy of identification, the discrete fast Fourier transform (DFFT) and the least-squares were used to process the signals of currents and voltages. A phase-voltage measuring method for motors was also proposed, which measured directly the actual conducting time of three upper switches in the inverter without need for a dead-time compensator. The validity, reliability and accuracy of the presented methods have been verified by the experiments on a VSI-fed IM drive system.
基金Supported by National Natural Science Foundation of China (No. 60074008, 60274007).
文摘Based on Lyapunov stability theory, a novel adaptive controller is designed for a class of chaotic systems .The parameters identification and synchronization of chaotic systems can be carried out simultaneously. The controller and the updating law of parameters identification are directly constructed by analytic formula. Simulation results with Chen’s system and R?ssler system show the effectiveness of the proposed controller.
