Structural-parametric model of an electroelastic actuator for nanomechanics

2020 ◽  
pp. 3-11
Author(s):  
S.M. Afonin
Keyword(s):  
Transfer Function ◽  
Piezoelectric Actuator ◽  
Transfer Functions ◽  
Piezoelectric Effect ◽  
Parametric Model ◽  
Elastic Compliance ◽  
Parametric Models ◽  
Piezo Actuator ◽  
Structural Scheme ◽  
Model Transfer

Structural-parametric models, structural schemes are constructed and the transfer functions of electro-elastic actuators for nanomechanics are determined. The transfer functions of the piezoelectric actuator with the generalized piezoelectric effect are obtained. The changes in the elastic compliance and rigidity of the piezoactuator are determined taking into account the type of control. Keywords electro-elastic actuator, piezo actuator, structural-parametric model, transfer function, parametric structural scheme

Structural Schemes and Structural-Parametric Models of Electroelastic Actuators for Nanomechatronics Systems

2019 ◽  
Vol 20 (4) ◽  
pp. 219-229
Author(s):  
S. M. Afonin
Keyword(s):  
Wave Equation ◽  
Control Systems ◽  
Dynamic Characteristics ◽  
Transfer Functions ◽  
Piezoelectric Effect ◽  
Parametric Model ◽  
Parametric Models ◽  
Physical Parameters ◽  
Static And Dynamic Characteristics ◽  
Automatic Control Systems

The parametric structural schemes, structural-the parametric models and the transfer functions of the electroelastic actuators for the nanomechatronics systems are obtained. The transfer functions of the piezoactuator are determined under the generalized piezoelectric effect. The changes in the elastic compliance and the stiffness of the piezoactuator are found, taking into account the type of control. The decision wave equation and the structural-parametric models of the electroelastic actuators are obtained. Effects of the geometric and physical parameters of the electroelastic actuators and the external load on its static and dynamic characteristics are determined. The parameteric structural schemes for the electroelastic actuators for the nanomechatronics systems are obtained. The transfer functions are determined. For calculation of the automatic control systems for the nanometric movements with the electroelastic actuators are obtained the parametric structural schemes and the transfer functions of actuators. Static and dynamic characteristics of the electroelastic actuators are determined. The application of electroelastic actuators solves problems of the precise matching in microelectronics and nanotechnology, compensation of temperature and gravitational deformations, atmospheric turbulence by wave front correction. By solving the wave equation with allowance for the corresponding equations of the piezoelectric effect, the boundary conditions on loaded working surfaces of the electroelastic actuator, the strains along the coordinate axes, it is possible to construct the structural parametric model of the actuator. The transfer functions and the parametric structural schemes of the electroelastic actuator are obtained from the equations describing the corresponding structural parametric models and taking into account the opposed electromotive force of the electroelastic actuator for the nanomechatronics systems.

Electromechanical Modeling of Hybrid Piezohydraulic Actuator System for Active Vibration Control

1997 ◽  
Vol 119 (1) ◽  
pp. 10-18 ◽  
Author(s):  
Punan Tang ◽  
Alan B. Palazzolo ◽  
Albert F. Kascak ◽  
Gerald T. Montague
Keyword(s):  
Transfer Function ◽  
Vibration Control ◽  
Piezoelectric Actuator ◽  
Closed Loop ◽  
Transfer Functions ◽  
Active Vibration Control ◽  
Space Representation ◽  
Electromechanical Modeling ◽  
Actuator System ◽  
Active Vibration

Electromechanical modeling of a hybrid piezohydraulic actuator system for active vibration control was developed. The transfer function of piezoelectric actuator was derived from the electromechanical potential energy law. This transfer function represents the dynamic relationship between input electric voltage and piezoelectric actuator displacement. The hydraulic actuator was characterized by impedance matching in which its transfer functions were experimentally determined. The transfer functions were transformed into a state-space representation, which is easily assembled into an active vibration control (AVC) closed-loop simulation. Good correlation of simulation and test was achieved for the hybrid system. A closed-loop dynamic simulation for imbalance response with/without AVC of a spinning rotor test rig at NASA Lewis was performed and showed excellent agreement with test results. The simulation couples the piezoelectric, hydraulic, and structural (rotor) components.

scholarly journals Electro Magneto Elastic Actuator for Nanoscience

2019 ◽  
Vol 3 (1) ◽  
Keyword(s):  
Mathematical Model ◽  
Transfer Function ◽  
External Load ◽  
Transfer Functions ◽  
Physical Parameters ◽  
Structural Scheme ◽  
Matrix Transfer Function ◽  
The Matrix ◽  
The Mathematical Model

The mathematical model, the structural scheme, the matrix transfer function, the characteristics of the electro magneto elastic actuator is obtained. The transfer functions of the magneto elastic actuator are described the characteristics of the actuator with regard to its physical parameters and external load.

Analytic integration of contrast transfer functions

1988 ◽  
Vol 46 ◽  
pp. 822-823
Author(s):  
Peter Rez
Keyword(s):  
Wave Function ◽  
Transfer Function ◽  
Transfer Functions ◽  
Spherical Aberration ◽  
Continuous Distribution ◽  
Objective Lens ◽  
Direction Parallel ◽  
Scattering Angle ◽  
Analytic Integration ◽  
Image Position

In high resolution microscopy the image amplitude is given by the convolution of the specimen exit surface wave function and the microscope objective lens transfer function. This is usually done by multiplying the wave function and the transfer function in reciprocal space and integrating over the effective aperture. For very thin specimens the scattering can be represented by a weak phase object and the amplitude observed in the image plane is1where fe (Θ) is the electron scattering factor, r is a postition variable, Θ a scattering angle and x(Θ) the lens transfer function. x(Θ) is given by2where Cs is the objective lens spherical aberration coefficient, the wavelength, and f the defocus.We shall consider one dimensional scattering that might arise from a cross sectional specimen containing disordered planes of a heavy element stacked in a regular sequence among planes of lighter elements. In a direction parallel to the disordered planes there will be a continuous distribution of scattering angle.

Trombone Transfer Functions: Comparison Between Frequency-Swept Sine Wave and Human Performer Input

2012 ◽  
Vol 37 (4) ◽  
pp. 447-454
Author(s):  
James W. Beauchamp
Keyword(s):  
Transfer Function ◽  
Transfer Functions ◽  
Cutoff Frequency ◽  
Sine Wave ◽  
Nonlinear Propagation ◽  
Linear Filter ◽  
Wave System ◽  
General Effect ◽  
Filter Characteristic ◽  
High Pass

Abstract Source/filter models have frequently been used to model sound production of the vocal apparatus and musical instruments. Beginning in 1968, in an effort to measure the transfer function (i.e., transmission response or filter characteristic) of a trombone while being played by expert musicians, sound pressure signals from the mouthpiece and the trombone bell output were recorded in an anechoic room and then subjected to harmonic spectrum analysis. Output/input ratios of the signals’ harmonic amplitudes plotted vs. harmonic frequency then became points on the trombone’s transfer function. The first such recordings were made on analog 1/4 inch stereo magnetic tape. In 2000 digital recordings of trombone mouthpiece and anechoic output signals were made that provide a more accurate measurement of the trombone filter characteristic. Results show that the filter is a high-pass type with a cutoff frequency around 1000 Hz. Whereas the characteristic below cutoff is quite stable, above cutoff it is extremely variable, depending on level. In addition, measurements made using a swept-sine-wave system in 1972 verified the high-pass behavior, but they also showed a series of resonances whose minima correspond to the harmonic frequencies which occur under performance conditions. For frequencies below cutoff the two types of measurements corresponded well, but above cutoff there was a considerable difference. The general effect is that output harmonics above cutoff are greater than would be expected from linear filter theory, and this effect becomes stronger as input pressure increases. In the 1990s and early 2000s this nonlinear effect was verified by theory and measurements which showed that nonlinear propagation takes place in the trombone, causing a wave steepening effect at high amplitudes, thus increasing the relative strengths of the upper harmonics.

scholarly journals Determination of the Optimal Neural Network Transfer Function for Response Surface Methodology and Robust Design

2021 ◽  
Vol 11 (15) ◽  
pp. 6768
Author(s):  
Tuan-Ho Le ◽  
Hyeonae Jang ◽  
Sangmun Shin
Keyword(s):  
Response Surface Methodology ◽  
Transfer Function ◽  
Response Surface ◽  
Robust Design ◽  
Transfer Functions ◽  
Desirability Function ◽  
Likelihood Estimation ◽  
Statistical Simulation ◽  
Screening Procedure ◽  
Function Estimation

Response surface methodology (RSM) has been widely recognized as an essential estimation tool in many robust design studies investigating the second-order polynomial functional relationship between the responses of interest and their associated input variables. However, there is scope for improvement in the flexibility of estimation models and the accuracy of their results. Although many NN-based estimations and optimization approaches have been reported in the literature, a closed functional form is not readily available. To address this limitation, a maximum-likelihood estimation approach for an NN-based response function estimation (NRFE) is used to obtain the functional forms of the process mean and standard deviation. While the estimation results of most existing NN-based approaches depend primarily on their transfer functions, this approach often requires a screening procedure for various transfer functions. In this study, the proposed NRFE identifies a new screening procedure to obtain the best transfer function in an NN structure using a desirability function family while determining its associated weight parameters. A statistical simulation was performed to evaluate the efficiency of the proposed NRFE method. In this particular simulation, the proposed NRFE method provided significantly better results than conventional RSM. Finally, a numerical example is used for validating the proposed method.

Error analyses of a Multi-Input-Multi-Output cantilever beam test

2021 ◽  
pp. 107754632110337
Author(s):  
Arup Maji ◽  
Fernando Moreu ◽  
James Woodall ◽  
Maimuna Hossain
Keyword(s):  
Transfer Function ◽  
Frequency Domain ◽  
Cantilever Beam ◽  
Transfer Functions ◽  
Linear Superposition ◽  
Transfer Function Matrix ◽  
Error Analyses ◽  
Pseudo Inverse ◽  
Function Matrix

Multi-Input-Multi-Output vibration testing typically requires the determination of inputs to achieve desired response at multiple locations. First, the responses due to each input are quantified in terms of complex transfer functions in the frequency domain. In this study, two Inputs and five Responses were used leading to a 5 × 2 transfer function matrix. Inputs corresponding to the desired Responses are then computed by inversion of the rectangular matrix using Pseudo-Inverse techniques that involve least-squared solutions. It is important to understand and quantify the various sources of errors in this process toward improved implementation of Multi-Input-Multi-Output testing. In this article, tests on a cantilever beam with two actuators (input controlled smart shakers) were used as Inputs while acceleration Responses were measured at five locations including the two input locations. Variation among tests was quantified including its impact on transfer functions across the relevant frequency domain. Accuracy of linear superposition of the influence of two actuators was quantified to investigate the influence of relative phase information. Finally, the accuracy of the Multi-Input-Multi-Output inversion process was investigated while varying the number of Responses from 2 (square transfer function matrix) to 5 (full-rectangular transfer function matrix). Results were examined in the context of the resonances and anti-resonances of the system as well as the ability of the actuators to provide actuation energy across the domain. Improved understanding of the sources of uncertainty from this study can be used for more complex Multi-Input-Multi-Output experiments.

Beyond Deep Learning: An Econometric Example

2020 ◽  
Vol 28 (Supp01) ◽  
pp. 31-38 ◽  
Author(s):  
Ruofan Liao ◽  
Paravee Maneejuk ◽  
Songsak Sriboonchitta
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Prediction Models ◽  
Original Data ◽  
Parametric Model ◽  
Parametric Models ◽  
The Past ◽  
Currency Exchange ◽  
Currency Exchange Rate ◽  
Linear And Nonlinear

In the past, in many areas, the best prediction models were linear and nonlinear parametric models. In the last decade, in many application areas, deep learning has shown to lead to more accurate predictions than the parametric models. Deep learning-based predictions are reasonably accurate, but not perfect. How can we achieve better accuracy? To achieve this objective, we propose to combine neural networks with parametric model: namely, to train neural networks not on the original data, but on the differences between the actual data and the predictions of the parametric model. On the example of predicting currency exchange rate, we show that this idea indeed leads to more accurate predictions.

Optical Measurement of Local and Global Transfer Functions for Equivalence Ratio Fluctuations in a Turbulent Swirl Flame

2013 ◽  
Author(s):  
Bernhard C. Bobusch ◽  
Bernhard Ćosić ◽  
Jonas P. Moeck ◽  
Christian Oliver Paschereit
Keyword(s):  
Transfer Function ◽  
Heat Release ◽  
Heat Release Rate ◽  
Release Rate ◽  
Equivalence Ratio ◽  
Transfer Functions ◽  
Optical Measurement ◽  
Low Frequencies ◽  
Fuel Flow ◽  
Calibration Measurement

Equivalence ratio fluctuations are known to be one of the key factors controlling thermoacoustic stability in lean premixed gas turbine combustors. The mixing and thus the spatio-temporal evolution of these perturbations in the combustor flow is, however, difficult to account for in present low-order modeling approaches. To investigate this mechanism, experiments in an atmospheric combustion test rig are conducted. To assess the importance of equivalence ratio fluctuations in the present case, flame transfer functions for different injection positions are measured. By adding known perturbations in the fuel flow using a solenoid valve, the influence of equivalence ratio oscillations on the heat release rate is investigated. The spatially and temporally resolved equivalence ratio fluctuations in the reaction zone are measured using two optical chemiluminescence signals, captured with an intensified camera. A steady calibration measurement allows for the quantitative assessment of the equivalence ratio fluctuations in the flame. This information is used to obtain a mixing transfer function, which relates fluctuations in the fuel flow to corresponding fluctuations in the equivalence ratio of the flame. The current study focuses on the measurement of the global, spatially integrated, transfer function for equivalence ratio fluctuations and the corresponding modeling. In addition, the spatially resolved mixing transfer function is shown and discussed. The global mixing transfer function reveals that despite the good spatial mixing quality of the investigated generic burner, the ability to damp temporal fluctuations at low frequencies is rather poor. It is shown that the equivalence ratio fluctuations are the governing heat release rate oscillation response mechanism for this burner in the low-frequency regime. The global transfer function for equivalence ratio fluctuations derived from the measurements is characterized by a pronounced low-pass characteristic, which is in good agreement with the presented convection–diffusion mixing model.

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