Papers by Keyword: Parameter Estimation

Abstract: This paper explores the versatility of Bouc-Wen hysteresis model in simulating the dynamic behaviour of magnetorheological elastomer (MRE) material. Bouc-Wen model have been used in many field of science including modelling the hysteresis phenomenon happen in magnetic material, elastomer, base isolation of structures and many more. Introduced by the Robert Bouc, this nonlinear hysteretic model has been modified by many researchers to suit different applications. Compression testing of MRE material under high strain amplitude produces nonlinear hysteresis curve based on stress-strain data. Bouc-Wen hysteretic model has been found to be able to simulate the hysteresis curve of MRE material using parameter identification method within MATLAB Simulink.

Abstract: Since the emergence of the van der Waals model, a lot of equations of state have been proposed to represent the pressure-volume-temperature (PVT) behavior of pure compounds, as is the case with GEOS3C, which is a form of generalized cubic equation of state that uses a temperature function dependent on three adjustable parameters. As the predictive capacity of an equation of state is directly related to the use of adequate and efficient methods for estimating the model's parameters, it is advised to use the multiobjective optimization in this class of problems, due to the conflicting nature of the objective functions. In this context, a MOPSO algorithm, based on the Pareto dominance principle, is used to estimate the parameters of the GEOS3C, through the minimization of the deviations in the prediction of different thermodynamic properties: saturation pressure, saturated liquid volume, enthalpy of vaporization and isobaric heat capacity, in order to assess whether it is possible to obtain a model parameterization that is adequate to represent the different properties simultaneously. Comparisons with experimental data available in the literature are performed showing that multiobjective optimization offers new perspectives for improvements in the parameters estimation of equations of state compared to traditional methods.

Abstract: Since the emergence of van der Waals equation of state, several equations have been proposed to represent the behavior of pure compounds and mixtures, such as GEOS, which is a new generalized cubic equation of state form that employs a temperature function dependent on two or three adjustable parameters. Recently, multiobjective optimization has started to be applied in equations of state for parameters estimation, due to the conflicting nature of the objective functions. This methodology is attractive because it can be used to compare different models or variants of the same problem, through the trade-off analysis of the so-called Pareto front. In this context, the multiobjective PSO algorithm, based on the Pareto dominance principle, is used in this work for estimating the parameters of the generalized cubic equation of state, by fitting its results to synthetic experimental data of vapor pressure and saturated liquid volume. The performance of the new estimated parameters of the three temperature functions is investigated through the calculation of thermodynamic properties of interest in industry and academia. In addition, comparisons against real experimental data available in the literature are performed.

Abstract: This paper presents a new approach for reliability test sampling plan of Railway equipment. Based on the interval censored failure data, the mean rank order method is used for data pre-process and the least square method is used for fitting the parameters of Weibull distribution, where, the best estimations of distribution parameters are derived. The sampling inspection plan for interval censored data is established when the lifetime follows the Weibull distribution. In the case study, we applied the proposed method to design the reliability test sampling plan of an electric multiple units.

Abstract: The aim of this project is to develop parameter estimation for dynamic model of distribution network cell (DNC) using fuzzy system. The parameter value was updated through adaptive neuro-fuzzy inference system (ANFIS). The active and reactive power responses from the fuzzy model were compared with the response from the full DNC model at various types of disturbances. The response of full DNC model was obtained from the UK 11 kV distribution network model. The model was built in DigSILENT PowerFactory software. The results obtained shown that the fuzzy model was more simple as only a few parameters involved in developing the equivalent model. This simplicity was reflected in the low computational time. In conclusion, the parameter estimation using fuzzy system was successfully developed.

Abstract: In this work, a three-parameter Weibull methodology for fracture prediction of brittle and ductile materials is presented. The approach proposed requires previous definition of the failure criterion to be applied. The parameter estimation is achieved for proportionally and non-proportionally increasing stresses. The case of two concurrent failure types is also handled. The resulting primary failure distribution can be expressed as a function of an effective size (length, area or volume) for its subsequent application in practical design of specimens or components using FEM.

Abstract: This paper proposed the Weighted Least Square method (WLS method) to identify the output filter of three-phase PWM converter, which incorporates the signal processing as well as mathematical techniques into conventional Least Square method. It sets different weights to different measurements according to the phase where it locates, based on the discovery of the correlation between accuracy and phase of current. The algorithm is tested in both simulation and experimental environment, and the results validate that proposed method gives accurate estimation in steady state, and can response within 10ms in when grid voltage drops. This method can work under both balanced and unbalanced operating conditions, therefore provides a powerful tool for various control strategies to better understand the operating conditions. Compared with the invasive method, which intentionally inject a series of white noise in the system, proposed WLS method does not bring any turbulence, while compared with conventional Least Square method, it possesses better stability as well as higher accuracy.

Abstract: The problem of target localization and parameter estimation in wideband bistatic Multiple-Input Multiple-Output (MIMO) radar system is considered. In this paper, we use a novel approach to estimate Doppler stretch and time delay in fractional Fourier transform (FRFT) domain. We also develop two sub-array models to accurately estimate the direction-of-departure (DOD) and the direction-of-arrival (DOA). Furthermore, the Cramér-Rao bound for target parameter estimation is derived and computed in closed form. Parameter estimation performances are evaluated and studied theoretically and via simulations

Abstract: The electric-field, caused by corrosion and prevention of corrosion method was used to overcome the deficiency for acoustic detection system in underwater target detection. The research on electric-field detection was based on electric-field sensor linear array and digital signal processing technology. Firstly, the electric-field distribution feature was simulated by electric-dipole model in shallow sea. The electric-field sensor vertical line arrays were laid regularly to obtain electric-field signal. Then, the generalized likelihood ratio (GLRT) method was used to process target detection and parameter estimation. Finally, the simulation experiment was done and indicated that the method could accurately realize parameter estimation on target initial position, velocity and direction, etc all when the signal-to-noise ratio (SNR) was greater than 0dB. The error became larger as the SNR reduced. The GLRT still could detect target when the SNR reduced to-10dB and partial parameter estimation error became larger.

Abstract: For the airborne weather radar signal processing, the intensity of the meteorological targets is represented by the physical quantity called reflectivity factor. When observing the middle-or long-range meteorological targets at low altitude from a high-altitude radar platform, due to the incomplete beam filling, the retrieval result of the reflectivity factor is much less than the actual value. In this paper, we firstly introduce a beam filling coefficient into the weather radar equation and then present its estimation method based on the real-time radar operating parameters. The validity of the proposed method is then verified by processing the raw-data of the simulated meteorological targets.