scholarly journals SOLVING THE PROBLEM OF ROAD AND RAIL TRANSPORT OBJECTS WEIGHING IN MOTION

2021 ◽  
Vol 8 ◽  
pp. 143-149
Author(s):  
Vladislav D. Rachkov ◽  
Victor M. Tissen
Keyword(s):  
Input Signal ◽  
Simulation Modeling ◽  
Parametric Identification ◽  
Strain Gauges ◽  
Identification Algorithm ◽  
Signal Shape ◽  
Oscillatory Circuit ◽  
Signal Parameters ◽  
Processing Data ◽  
Dynamic Weighing

The algorithm for processing data obtained from strain gauges during dynamic weighing of a railway or auto car passing through the weighing platform using the parametric identification method is considered. The model of the second-order oscillatory circuit is presented and the method for identifying its coefficients with the transformation to the Volterra integral equation of the 2nd kind is shown. An idealized simulation model of the oscillatory link is proposed, which allows to obtain the output signal shape depending on its coefficients and the input signal parameters. Using the results of simulation modeling, the effectiveness of the proposed identification algorithm for determining the input signal parameters is shown.

scholarly journals Parametric identification algorithm for asynchronous electric motor inverter on the switching intervals of power transistors

2019 ◽  
Vol 124 ◽  
pp. 02017
Author(s):  
A. Andreev ◽  
M. Andreev ◽  
D. Kolesnihenko ◽  
R.R. Dyganova ◽  
G.T. Merzadinova ◽  
...  
Keyword(s):  
Real Time ◽  
Electric Drive ◽  
Electric Motor ◽  
Parametric Identification ◽  
Identification Algorithm ◽  
Power Transistors ◽  
Asynchronous Electric Drive ◽  
Subsequent Calculation ◽  
Asynchronous Electric Motor ◽  
A Current

The authors propose an algorithm for identifying the parameters of a controlled asynchronous electric drive in real time, which provides calculation of stator and rotor resistances which change as a function of temperature. The algorithm is based on the analysis of a current tube of electric motor phase with the subsequent calculation of resistances.

Parametric Identification of Abkowitz Model for Ship Maneuvering Motion by Using Partial Least Squares Regression

2015 ◽  
Vol 137 (3) ◽  
Author(s):  
Yin Jian-Chuan ◽  
Zou Zao-Jian ◽  
Xu Feng
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Parametric Identification ◽  
Small Sample ◽  
High Dimensionality ◽  
Pls Regression ◽  
Ship Maneuvering ◽  
Processing Data ◽  
Hydrodynamic Derivatives ◽  
Maneuvering Motion

Partial least squares (PLS) regression is used for identifying the hydrodynamic derivatives in the Abkowitz model for ship maneuvering motion. To identify the dynamic characteristics in ship maneuvering motion, the derivatives of hydrodynamic model's outputs are set as the target output of the PLS identification model. To verify the effectiveness of PLS parametric identification method in processing data with high dimensionality and heavy multicollinearity, the identified results of the hydrodynamic derivatives from the simulated 20 deg/20 deg zigzag test are compared with the planar motion mechanism (PMM) test results. The performance of PLS regression is also compared with that of the conventional least squares (LS) regression using the same dataset. Simulation results show the satisfactory identification and generalization performances of PLS regression and its superiority in comparison with the LS method, which demonstrates its capability in processing measurement data with high dimensionality and heavy multicollinearity, especially in processing data with small sample size.

scholarly journals Parametric Identification of Chaotic Base-Excited Double Pendulum Experiment

2004 ◽  
Author(s):  
Yang Liang ◽  
B. F. Feeny
Keyword(s):  
Harmonic Balance ◽  
Parametric Identification ◽  
Identification Algorithm ◽  
Double Pendulum ◽  
Unstable Periodic Orbits ◽  
Identification Process ◽  
Response Data ◽  
Regression Techniques ◽  
Linearized System ◽  
Pendulum Experiment

An improved parametric identification of chaotic systems was investigated for a double pendulum. From recorded experimental response data, the unstable periodic orbits were extracted and later used in a harmonic balance identification process. By applying digital filtering, digital differentiation and linear regression techniques for optimization, the results were improved. Verification of the related simulation system and linearized system also corroborated the success of the identification algorithm.

Parametric Identification of Ship Maneuvering Models by Using Support Vector Machines

2009 ◽  
Vol 53 (01) ◽  
pp. 19-30 ◽  
Author(s):  
W. L. Luo ◽  
Z. J. Zou
Keyword(s):  
Support Vector Machines ◽  
Predictive Ability ◽  
Parametric Identification ◽  
Inner Product ◽  
Support Vector ◽  
Identification Algorithm ◽  
Hydrodynamic Coefficients ◽  
Ship Maneuvering ◽  
Vector Machines ◽  
Maneuvering Motion

System identification combined with free-running model tests or full-scale trials is one of the effective methods to determine the hydrodynamic coefficients in the mathematical models of ship maneuvering motion. By analyzing the available data, including rudder angle, surge speed, sway speed, yaw rate, and so forth, a method based on support vector machines (SVM) to estimate the hydrodynamic coefficients is proposed for conventional surface ships. The coefficients are contained in the expansion of the inner product of a linear kernel function. Predictions of maneuvering motion are conducted by using the parameters identified. The results of identification and simulation demonstrate the validity of the identification algorithm proposed. The simultaneous drift and multicollinearity are diminished by introducing an additional ramp signal to the training samples. Comparison between the simulated and predicted motion variables from different maneuvers shows good predictive ability of the trained SVM.

On Response Prediction of Degrading Structures

2005 ◽  
Author(s):  
C. H. Ng ◽  
N. Ajavakom ◽  
F. Ma
Keyword(s):  
Structure Prediction ◽  
Hysteresis Loops ◽  
Response Prediction ◽  
Parametric Identification ◽  
Practical Significance ◽  
Identification Algorithm ◽  
Hysteretic Model ◽  
Sea Waves ◽  
Future Performance ◽  
Brute Force Approach

All structures degrade when acted upon by cyclic forces associated with earthquakes, high winds, and sea waves. Identification and prediction of degradation is thus a problem of considerable practical significance in the field of engineering mechanics. Under cyclic excitations, system degradation manifests itself in the evolution of the associated hysteresis loops. In this paper, a robust identification algorithm is devised to generate hysteretic models of a deteriorating structure from its experimental load-displacement traces. This algorithm is based upon the generalized Bouc-Wen model and the latest theory of differential evolution, streamlined through global sensitivity analysis. It can account for strength degradation, stiffness degradation, and pinching characteristics in the evolution of hysteretic traces, whereby earlier studies in parametric identification of hysteresis are extended. In addition, it is shown experimentally that a hysteretic model obtained by identification can be used to predict the future performance of a degrading structure. Prediction of degradation through identification is a brute-force approach that offers a close representation of reality. There is not any method based upon the fundamental postulates of mechanics that can predict the response of a degrading structure well beyond its linear range.

scholarly journals Carreau's Rheological Model and A.N. Tikhonov’s Regularization Method: Parametric Identification Based on a CFD model

2021 ◽  
pp. 615-627
Author(s):  
Anatoly Khvostov ◽  
Gazibeg Magomedov ◽  
Victor Ryazhskikh ◽  
Aleksey Kovalev ◽  
Aleksey Zhuravlev ◽  
...  
Keyword(s):  
Regularization Method ◽  
Rheological Model ◽  
Three Dimensional ◽  
Parametric Identification ◽  
Rheological Parameters ◽  
Identification Algorithm ◽  
Cfd Model ◽  
Shear Rates ◽  
Tikhonov’S Regularization ◽  
Limiting Values

Introduction. Carreau's rheological model can describe the three-dimensional flows of non-Newtonian media. However, it requires modeling parameters for the viscosity of the medium at the limiting values of shear rates, which cannot be achieved by instrumental methods. The present article introduces a novel method that can identify the parameters of Carreau’s model using a regularization algorithm. Study objects and methods. The study featured fondant mass produced according to the traditional formulation for Creamy Fondant unglazed candies. Standard methods were used to describe the properties of the raw materials and semi-finished products, as well as methods of mathematical processing, modeling, and optimization. Results and its discussion. The research produced an algorithm based on A.N. Tikhonov’s regularization method of the parametric identification of Carreau's rheological model. The calculation residual was minimized by the viscometric measurements and the CFD model, which provided the calculation of the hydrodynamic flow regime at the limiting values of shear rates. The CFD model of a steady non-isothermal flow of a nonlinear viscous medium through a cylindrical capillary was based on the equations of conservation of mass, energy, and momentum. The rheological parameters of Carreau’s model were illustrated by the case of fondant mass. The error for the viscosity prediction did not exceed 14.07%. Conclusion. The parametric identification algorithm made it possible to evaluate the rheological parameters of structured liquid media with Carreau's rheological law in cases that lack experimental information on the behavior of the medium at limiting shear rates. The algorithm eliminated the computational problems typical of Ostwald and de Ville’s rheological model, which usually arise when solving practical problems of three-dimensional flows of non-Newtonian media with limiting viscosity values.

Dynamic response and vibration suppression of a cantilevered pipe conveying fluid under periodic excitation

2019 ◽  
Vol 25 (11) ◽  
pp. 1695-1705 ◽  
Author(s):  
Jiantao Li ◽  
Hua Deng ◽  
Wenjun Jiang
Keyword(s):  
Input Signal ◽  
Vibration Suppression ◽  
Feedforward Control ◽  
Structural Vibration ◽  
Pipeline System ◽  
Beam Model ◽  
Pipe Conveying Fluid ◽  
Theoretical Derivation ◽  
Signal Parameters ◽  
Conveying Fluid

A feedforward vibration suppression method is proposed for cantilever pipes conveying fluid. The fluid–structure interaction dynamic equation of the cantilever pipeline system is first established, based on the Euler–Bernoulli beam model. Next, the pulsation function of pipeline pressure is established using the Fourier series, which will serve as the input of the cantilever pipeline system. Then, analysis of transient response is carried out, and the relationship between input signal parameters and the end vibration is studied. Finally, a feedforward control strategy based on optimization of input signal parameters is proposed for minimizing the end vibration. Both theoretical derivation and experimental results in industrial equipment show that the proposed method (i.e., optimization of pressure function parameters) is effective and can suppress the structural vibration of a cantilever pipe conveying fluid.

Design of Master Controller Input Processing Method Based on LPC2292

2012 ◽  
Vol 182-183 ◽  
pp. 611-613
Author(s):  
Hui Yan ◽  
Lin Yu
Keyword(s):  
Operating System ◽  
Signal Processing ◽  
Input Signal ◽  
High Speed ◽  
External Environment ◽  
Processing Method ◽  
Input Processing ◽  
Processing Data ◽  
Master Controller ◽  
System Task

Because of external environment or man-made factors influence, the input signal and data of master elevator controller can not be judged and computed basis directly, but needs the corresponding processing .Therefore an operating system task should be assigned for input signal processing data, in order to deal with input signal. In this paper it realized switch quantity software filter and processing, analog quantities and high-speed counting input treatment of elevator master controller based on LPC2292 .

Non-Parametric Identification of Structural Nonlinearity with Limited Input and Output Measurements

2011 ◽  
Vol 243-249 ◽  
pp. 5403-5407 ◽  
Author(s):  
Ying Lei ◽  
Yan Wu
Keyword(s):  
Parametric Identification ◽  
Least Square ◽  
Frame Structure ◽  
Identification Algorithm ◽  
Recursive Least Square ◽  
Restoring Force ◽  
Input And Output ◽  
Structural Nonlinearity ◽  
Shear Frame ◽  
Non Parametric

In this paper, a technique is proposed for non-parametric identification of structural nonlinearity with limited input and output measurements. The identification algorithm is based on the classical Kalman estimator for the displacement and the velocity responses and the recursive least square estimation for the unmeasured excitation and the restoring force. Two different models are used to simulate nonlinear structures: One is a 4-storey shear-frame structure with excitation on the top floor and the nonlinearity occurs at the bottom floor. The other is also a 4-storey shear-frame structure with both excitation and the nonlinearity at the top floor. Two numerical examples are carried out for the two kinds of models. Bouc-Wen hysteretic models are used to simulate the nonlinear impact. The simulation results demonstrate the efficiency of the proposed technique with limited output measurements.

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