This paper develops an average power and energy method for the parametric identification of a system. The new method makes it possible to identify the parameters of a system depending only on its output information...This paper develops an average power and energy method for the parametric identification of a system. The new method makes it possible to identify the parameters of a system depending only on its output information, and can be used in both linear and non-linear systems.展开更多
The inherent strongly nonlinear and coupling performance of the Autonomous Underwater Vehicles （AUV）, maneuvering motion in the diving plane determines its difficulty in parametric identification. The motion paramet...The inherent strongly nonlinear and coupling performance of the Autonomous Underwater Vehicles （AUV）, maneuvering motion in the diving plane determines its difficulty in parametric identification. The motion parameters in diving plane are obtained by executing the Zigzag-like motion based on a mathematical model of maneuvering motion. A separate identification method is put forward for parametric identification by investigating the motion equations. Support vector machine is proposed to estimate the hydrodynamic derivatives by analyzing the data of surge, heave and pitch motions. Compared with the standard coefficients, the identified parameters show the validation of the proposed identification method. Sensitivity analysis based on numerical simulation demonstrates that poor sensitive derivative gives bad estimation results. Finally the motion simulation is implemented based on the dominant sensitive derivatives to verify the reconstructed model.展开更多
Bayesian estimation is applied to the analysis of backflow vortex instabilities in typical three-and four bladed liquid propellant rocket(LPR)engine inducers.The flow in the impeller eye is modeled as a set of equally...Bayesian estimation is applied to the analysis of backflow vortex instabilities in typical three-and four bladed liquid propellant rocket(LPR)engine inducers.The flow in the impeller eye is modeled as a set of equally intense and evenly spaced 2D axial vortices,located at the same radial distance from the axis and rotating at a fraction of the impeller speed.The circle theorem and the Bernoulli’s equation are used to predict the flow pressure in terms of the vortex number,intensity,rotational speed,and radial position.The theoretical spectra so obtained are frequency broadened to mimic the dispersion of the experimental data and parametrically fitted to the measured pressure spectra by maximum likelihood estimation with equal and independent Gaussian errors.The method is applied to three inducers,tested in water at room temperature and different loads and cavitation conditions.It successfully characterizes backflow instabilities using the signals of a single pressure transducer flush-mounted on the casing of the impeller eye,effectively by-passing the aliasing and data acquisition/reduction complexities of traditional multiple-sensor cross correlation methods.The identification returns the estimates of the model parameters and their standard errors,providing the information necessary for assessing the accuracy and statistical significance of the results.The flowrate is found to be the major factor affecting the backflow vortex instability,which,on the other hand,is rather insensitive to the occurrence of cavitation.The results are consistent with the data reported in the literature,as well as with those generated by the auxiliary models specifically developed for initializing the maximum likelihood searches and supporting the identification procedure.展开更多
Damping is critical for the roll motion response of a ship in waves. A common method for the assessment of damping in a ship’s rolling motion is to perform a free-decay experiment in calm water. In this paper, we pro...Damping is critical for the roll motion response of a ship in waves. A common method for the assessment of damping in a ship’s rolling motion is to perform a free-decay experiment in calm water. In this paper, we propose an approach for estimating nonlinear damping that involves a linear exponential analytical approximation of the experimental roll free-decay amplitudes, fol- lowed by parametric identification based on the asymptotic method. The restoring moment can be strongly nonlinear. To validate this method, we first analyzed numerically simulated roll free-decay data using rolling equations with two alternative parametric forms: linear-plus-quadratic and linear-plus-cubic damping. By doing so, we obtained accurate estimates of nonlinear damping coefficients, even for large initial roll amplitudes. Then, we applied the proposed method to real free-decay data obtained from a scale model of a bulk barrier, and found the simulated results to be in good agreement with the experimental data. Using only free-decay peak data, the proposed method can be used to estimate nonlinear roll-damping coefficients for conditions with a strongly nonlinear restoring moment and large initial roll amplitudes.展开更多
The article illustrates the application of Bayesian estimation to the identification of flow instabilities,with special reference to rotating cavitation,in a three-bladed axial inducer using the unsteady pressure read...The article illustrates the application of Bayesian estimation to the identification of flow instabilities,with special reference to rotating cavitation,in a three-bladed axial inducer using the unsteady pressure readings of a single transducer mounted on the casing just behind the leading edges of the impeller blades.The typical trapezoidal pressure distribution in the blade channels is parametrized and modulated in time and space for theoretically reproducing the expected pressure generated by known forms of cavitation instabilities(cavitation auto-oscillations and higher-order surge cavitation modes,n-lobed subsynchronous/synchronous/super-synchronous rotating cavitation).The Fourier spectra of the theoretical pressure so obtained in the rotating frame are transformed in the stationary frame,frequency broadened to better approximate the experimental results,and parametrically fitted by maximum likelihood estimation to the measured auto-correlation spectra.Each form of instability generates a characteristic distribution of sidebands in addition to its fundamental frequency.The identification makes use of this information for effective detection and characterization of multiple simultaneous flow instabilities with intensities spanning over about 20 db down to about 4 db signal-to-noise ratios.The same information also allows for effectively bypassing the aliasing limitations of traditional cross-correlation methods in the discrimination of multiple-lobed azimuthal instabilities from the measurements returned by arrays of equally spaced sensors.The method returns both the estimates of the model parameters and their standard deviations,providing the information needed for the assessment of the statistical significance of the results.The proposed approach represents therefore a promising tool for experimental research on flow instabilities in high-performance turbopumps.展开更多
In this paper, a geometric approach to fault detection and isolation （FDI） is applied to a Multiple-Input Multipie-Output （MIMO） model of a frame and the FDI results are compared to the ones obtained in the Single...In this paper, a geometric approach to fault detection and isolation （FDI） is applied to a Multiple-Input Multipie-Output （MIMO） model of a frame and the FDI results are compared to the ones obtained in the Single-Input Single-Output （SISO）, Multiple-Input Single-Output （MISO）, and Single-Input Multiple-Output （SIMO） cases. A proper distance function based on parameters obtained from parametric system identification method is used in the geometric approach. ARX （Auto Regressive with exogenous input） and VARX （Vector ARX） models with 12 parameters are used in all of the above-mentioned models. The obtained results reveal that by increasing the number of inputs, the classification errors reduce, even in the case of applying only one of the inputs in the computations. Furthermore, increasing the number of measured outputs in the FDI scheme results in decreasing classification errors. Also, it is shown that by using probabilistic space in the distance function, fault diagnosis scheme has better performance in comparison with the deterministic one.展开更多
We consider the problem of parameter estimation in both linear and nonlinear ordinary differential equation（ODE） models. Nonlinear ODE models are widely used in applications. But their analytic solutions are usually...We consider the problem of parameter estimation in both linear and nonlinear ordinary differential equation（ODE） models. Nonlinear ODE models are widely used in applications. But their analytic solutions are usually not available. Thus regular methods usually depend on repetitive use of numerical solutions which bring huge computational cost. We proposed a new two-stage approach which includes a smoothing method（kernel smoothing or local polynomial fitting） in the first stage, and a numerical discretization method（Eulers discretization method, the trapezoidal discretization method,or the Runge–Kutta discretization method） in the second stage. Through numerical simulations, we find the proposed method gains a proper balance between estimation accuracy and computational cost.Asymptotic properties are also presented, which show the consistency and asymptotic normality of estimators under some mild conditions. The proposed method is compared to existing methods in term of accuracy and computational cost. The simulation results show that the estimators with local linear smoothing in the first stage and trapezoidal discretization in the second stage have the lowest average relative errors. We apply the proposed method to HIV dynamics data to illustrate the practicability of the estimator.展开更多
文摘This paper develops an average power and energy method for the parametric identification of a system. The new method makes it possible to identify the parameters of a system depending only on its output information, and can be used in both linear and non-linear systems.
基金supported by the National Natural Science Foundation of China(Grant Nos.50979060,51079031)
文摘The inherent strongly nonlinear and coupling performance of the Autonomous Underwater Vehicles （AUV）, maneuvering motion in the diving plane determines its difficulty in parametric identification. The motion parameters in diving plane are obtained by executing the Zigzag-like motion based on a mathematical model of maneuvering motion. A separate identification method is put forward for parametric identification by investigating the motion equations. Support vector machine is proposed to estimate the hydrodynamic derivatives by analyzing the data of surge, heave and pitch motions. Compared with the standard coefficients, the identified parameters show the validation of the proposed identification method. Sensitivity analysis based on numerical simulation demonstrates that poor sensitive derivative gives bad estimation results. Finally the motion simulation is implemented based on the dominant sensitive derivatives to verify the reconstructed model.
文摘Bayesian estimation is applied to the analysis of backflow vortex instabilities in typical three-and four bladed liquid propellant rocket(LPR)engine inducers.The flow in the impeller eye is modeled as a set of equally intense and evenly spaced 2D axial vortices,located at the same radial distance from the axis and rotating at a fraction of the impeller speed.The circle theorem and the Bernoulli’s equation are used to predict the flow pressure in terms of the vortex number,intensity,rotational speed,and radial position.The theoretical spectra so obtained are frequency broadened to mimic the dispersion of the experimental data and parametrically fitted to the measured pressure spectra by maximum likelihood estimation with equal and independent Gaussian errors.The method is applied to three inducers,tested in water at room temperature and different loads and cavitation conditions.It successfully characterizes backflow instabilities using the signals of a single pressure transducer flush-mounted on the casing of the impeller eye,effectively by-passing the aliasing and data acquisition/reduction complexities of traditional multiple-sensor cross correlation methods.The identification returns the estimates of the model parameters and their standard errors,providing the information necessary for assessing the accuracy and statistical significance of the results.The flowrate is found to be the major factor affecting the backflow vortex instability,which,on the other hand,is rather insensitive to the occurrence of cavitation.The results are consistent with the data reported in the literature,as well as with those generated by the auxiliary models specifically developed for initializing the maximum likelihood searches and supporting the identification procedure.
基金support from the National Natural Science Foundation of China (No. 5160 9224)the Major Program of National Natural Science Foundation of China (No. 51490675)the Fundamental Research Funds for the Central Universities (No. 201513056)
文摘Damping is critical for the roll motion response of a ship in waves. A common method for the assessment of damping in a ship’s rolling motion is to perform a free-decay experiment in calm water. In this paper, we propose an approach for estimating nonlinear damping that involves a linear exponential analytical approximation of the experimental roll free-decay amplitudes, fol- lowed by parametric identification based on the asymptotic method. The restoring moment can be strongly nonlinear. To validate this method, we first analyzed numerically simulated roll free-decay data using rolling equations with two alternative parametric forms: linear-plus-quadratic and linear-plus-cubic damping. By doing so, we obtained accurate estimates of nonlinear damping coefficients, even for large initial roll amplitudes. Then, we applied the proposed method to real free-decay data obtained from a scale model of a bulk barrier, and found the simulated results to be in good agreement with the experimental data. Using only free-decay peak data, the proposed method can be used to estimate nonlinear roll-damping coefficients for conditions with a strongly nonlinear restoring moment and large initial roll amplitudes.
基金the European Space Agency under Contract No.4000113291/15/NL/RA.
文摘The article illustrates the application of Bayesian estimation to the identification of flow instabilities,with special reference to rotating cavitation,in a three-bladed axial inducer using the unsteady pressure readings of a single transducer mounted on the casing just behind the leading edges of the impeller blades.The typical trapezoidal pressure distribution in the blade channels is parametrized and modulated in time and space for theoretically reproducing the expected pressure generated by known forms of cavitation instabilities(cavitation auto-oscillations and higher-order surge cavitation modes,n-lobed subsynchronous/synchronous/super-synchronous rotating cavitation).The Fourier spectra of the theoretical pressure so obtained in the rotating frame are transformed in the stationary frame,frequency broadened to better approximate the experimental results,and parametrically fitted by maximum likelihood estimation to the measured auto-correlation spectra.Each form of instability generates a characteristic distribution of sidebands in addition to its fundamental frequency.The identification makes use of this information for effective detection and characterization of multiple simultaneous flow instabilities with intensities spanning over about 20 db down to about 4 db signal-to-noise ratios.The same information also allows for effectively bypassing the aliasing limitations of traditional cross-correlation methods in the discrimination of multiple-lobed azimuthal instabilities from the measurements returned by arrays of equally spaced sensors.The method returns both the estimates of the model parameters and their standard deviations,providing the information needed for the assessment of the statistical significance of the results.The proposed approach represents therefore a promising tool for experimental research on flow instabilities in high-performance turbopumps.
文摘In this paper, a geometric approach to fault detection and isolation （FDI） is applied to a Multiple-Input Multipie-Output （MIMO） model of a frame and the FDI results are compared to the ones obtained in the Single-Input Single-Output （SISO）, Multiple-Input Single-Output （MISO）, and Single-Input Multiple-Output （SIMO） cases. A proper distance function based on parameters obtained from parametric system identification method is used in the geometric approach. ARX （Auto Regressive with exogenous input） and VARX （Vector ARX） models with 12 parameters are used in all of the above-mentioned models. The obtained results reveal that by increasing the number of inputs, the classification errors reduce, even in the case of applying only one of the inputs in the computations. Furthermore, increasing the number of measured outputs in the FDI scheme results in decreasing classification errors. Also, it is shown that by using probabilistic space in the distance function, fault diagnosis scheme has better performance in comparison with the deterministic one.
基金Supported by NSFC(Grant Nos.11201317,11028103,11231010,11471223)Doctoral Fund of Ministry of Education of China(Grant No.20111108120002)+1 种基金the Beijing Municipal Education Commission Foundation(Grant No.KM201210028005)the Key Project of Beijing Municipal Educational Commission
文摘We consider the problem of parameter estimation in both linear and nonlinear ordinary differential equation（ODE） models. Nonlinear ODE models are widely used in applications. But their analytic solutions are usually not available. Thus regular methods usually depend on repetitive use of numerical solutions which bring huge computational cost. We proposed a new two-stage approach which includes a smoothing method（kernel smoothing or local polynomial fitting） in the first stage, and a numerical discretization method（Eulers discretization method, the trapezoidal discretization method,or the Runge–Kutta discretization method） in the second stage. Through numerical simulations, we find the proposed method gains a proper balance between estimation accuracy and computational cost.Asymptotic properties are also presented, which show the consistency and asymptotic normality of estimators under some mild conditions. The proposed method is compared to existing methods in term of accuracy and computational cost. The simulation results show that the estimators with local linear smoothing in the first stage and trapezoidal discretization in the second stage have the lowest average relative errors. We apply the proposed method to HIV dynamics data to illustrate the practicability of the estimator.
