Estimation of automobile-driver describing function from highway tests using the double steering wheel

The automobile-driver describing function for lateral position control was estimated for three subjects from frequency response analysis of straight road test results. The measurement procedure employed an instrumented full size sedan with known steering response characteristics, and equipped with a lateral lane position measuring device based on video detection of white stripe lane markings. Forcing functions were inserted through a servo driven double steering wheel coupling the driver to the steering system proper. Random appearing, Gaussian, and transient time functions were used. The quasi-linear models fitted to the random appearing input frequency response characterized the driver as compensating for lateral position error in a proportional, derivative, and integral manner. Similar parameters were fitted to the Gabor transformed frequency response of the driver to transient functions. A fourth term corresponding to response to lateral acceleration was determined by matching the time response histories of the model to the experimental results. The time histories show evidence of pulse-like nonlinear behavior during extended response to step transients which appear as high frequency remnant power

Finite element analysis of fluid-filled elastic piping systems

Two finite element procedures are described for predicting the dynamic response of general 3-D fluid-filled elastic piping systems. The first approach, a low frequency procedure, models each straight pipe or elbow as a sequence of beams. The contained fluid is modeled as a separate coincident sequence axial members (rods) which are tied to the pipe in the lateral direction. The model includes the pipe hoop strain correction to the fluid sound speed and the flexibility factor correction to the elbow flexibility. The second modeling approach, an intermediate frequency procedure, follows generally the original Zienkiewicz-Newton scheme for coupled fluid-structure problems except that the velocity potential is used as the fundamental fluid unknown to symmetrize the coefficient matrices. From comparisons of the beam model predictions to both experimental data and the 3-D model, the beam model is validated for frequencies up to about two-thirds of the lowest fluid-filled labor pipe mode. Accurate elbow flexibility factors are seen to be crucial for effective beam modeling of piping systems

The matrix exponential in transient structural analysis

The primary usefulness of the presented theory is in the ability to represent the effects of high frequency linear response with accuracy, without requiring very small time steps in the analysis of dynamic response. The matrix exponential contains a series approximation to the dynamic model. However, unlike the usual analysis procedure which truncates the high frequency response, the approximation in the exponential matrix solution is in the time domain. By truncating the series solution to the matrix exponential short, the solution is made inaccurate after a certain time. Yet, up to that time the solution is extremely accurate, including all high frequency effects. By taking finite time increments, the exponential matrix solution can compute the response very accurately. Use of the exponential matrix in structural dynamics is demonstrated by simulating the free vibration response of multi degree of freedom models of cantilever beams

Ropeway roller batteries dynamics. Modeling, identification, and full-scale validation

A parametric mechanical model based on a Lagrangian formulation is here proposed to predict the dynamic response of roller batteries during the vehicles transit across the so-called compression towers in ropeways transportation systems. The model describes the dynamic interaction between the ropeway substructures starting from the modes and frequencies of the system to the forced dynamic response caused by the vehicles transit. The analytical model is corroborated and validated via an extensive experimental campaign devoted to the dynamic characterization of the roller battery system. The data acquired on site via a custom-design sensor network allowed to identify the frequencies and damping ratios by employing the Frequency Domain Decomposition (FDD) method. The high fidelity modeling and the system identification procedure are discussed

Measurement Points selection strategy to update models in frequency domain

In model updating procedures, the experimental data provide information for a configuration error modelling. The selection of the measurement DOFs in the experimental frequency response function should make the updating procedure as capable as possible of detecting configuration mismodelling in the initial model. The selection of the measurement DOFs should be sensitive to the effects of the possible configuration mismodelling in the model. For the model updating procedure, the experimental data should be measured in such a way that the modified model resulting from the updating procedure is the most likely to be reckoned as an updated model. This paper proposes a technique for selecting measurement points that should provide the best structural information for updating. The selected measurement points would define the defects that can be detected. The proposed method is based on the derivative of the frequency response function which materializes the participation of each element on the variation of the measured frequency response

Identification of non-proportional structural damping using experimental modal analysis data

A verified computational model of a complex structure is crucial for reliable vibro-acoustic simulations. Mass and stiffness matrices of such a computational model may be constructed correctly, provided all the design information is available. Since it is an unknown, the damping matrix is usually populated through mathematical models based on some assumptions. In the current study, it is proposed to use the identified non-proportional structural damping matrix in the computational model. Structural damping matrix can be identified using the complex frequency response functions obtained from experimental modal analysis data. No matter what type of a damping mechanism a structure has; proportional or non-proportional, the frequency response functions of the system can be measured. First, the calculation procedure for the non-proportional structural damping matrix is explained. The damping matrix of an analytical model is identified successfully using the proposed procedure. The same procedure is then applied through a case study. Computational model of a test vehicle is constructed. Next, the test vehicle is subjected to a modal test to measure the frequency response functions of the structure. Incompleteness of the measured data and the requirements of the procedure are discussed, as well. The described procedure can be used in any model updating framework

Hand-arm equal sensation curves for steering wheel rotational vibration

The present study has established equal sensation curves for steering wheel handarm rotational vibration. Psychophysical response tests of 20 participants were performed using the category-ratio Borg CR10 scale procedure. The test stimuli used were sinusoidal vibrations at 22 third octave band centre frequencies in the range from 3 to 400 Hz, with amplitudes in the range from 0.06 to 30 m/s2 r.m.s. A multivariate regression analysis was performed on the mean Borg CR10 intensity values as a function of the two independent parameters of the vibration frequency and amplitude. The results suggested a nonlinear dependency of the perceived intensity on both the steering wheel rotational vibration frequency and amplitude. A sixth-order polynomial model has been proposed as a best fit regression model

The low-noise optimisation method for gearbox in consideration of operating conditions

This paper presents a comprehensive procedure to calculate the steady dynamic response and the noise radiation generated from a stepping-down gearbox. In this process, the dynamic model of the cylindrical gear transmission system is built with the consideration of the time-varying mesh stiffness, gear errors and bearing supporting, while the data of dynamic bearing force is obtained through solving the model. Furthermore, taking the data of bearing force as the excitation, the gearbox vibrations and noise radiation are calculated by numerical simulation, and then the time history of node dynamic response, noise spectrum and resonance frequency range of the gearbox are obtained. Finally, the gearbox panel acoustic contribution at the resonance frequency range is calculated. Based on the conclusions from the gearbox panel acoustic contribution analyses and the mode shapes, two gearbox stiffness improving plans have been studied. By contrastive analysis of gearbox noise radiation, the effectiveness of the improving plans is confirmed. This study has provided useful theoretical guideline to the gearbox design

Experimental High-Frequency Parameter Identification of AC Electrical Motors

In order to predict conducted electromagnetic interference in inverter-motor drive systems, high-frequency (HF) motor models are requested and the involved parameters have to be available. In previous studies, the authors have presented an accurate HF model for induction motors and they have defined the procedures to identify the model parameters. In this paper, these results are extended to several types and sizes of industrial ac motors such as induction, synchronous reluctance (without interior permanent magnets), and brushless motors. The model parameter-identification procedure has been improved, and it is based on a least-squares data fitting applied to the measured magnitude and phase-frequency-response curves of the phase-to-ground and the phase-to-neutral impedances. The aim of this paper is to provide quick indications to select the suitable values of the HF model parameters, with reference to the size and type of the ac motor, to evaluate the HF voltage and current components in inverted-fed ac motor system

Foreword

This paper considers identification of unknown parameters in elastic dynamic models of industrial robots. Identifying such models is a challenging task since an industrial robot is a multivariable, nonlinear, resonant, and unstable system. Unknown parameters (mainly spring-damper pairs) in a physically parameterized nonlinear dynamic model are identified in the frequency domain, using estimates of the nonparametric frequency response function (FRF) in different robot configurations/positions. The nonlinear parametric robot model is linearized in the same positions and the optimal parameters are obtained by minimizing the discrepancy between the nonparametric FRFs and the parametric FRFs (the FRFs of the linearized parametric robot model). In order to accurately estimate the nonparametric FRFs, the experiments must be carefully designed. The selection of optimal robot configurations for the experiments is also part of the design. Different parameter estimators are compared and experimental results show the usefulness of the proposed identification procedure. The weighted logarithmic least squares estimator achieves the best result and the identified model gives a good global description of the dynamics in the frequency range of interest