scholarly journals Study on an Integral Algorithm of Load Identification Based on Displacement Response

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6403
Author(s):  
Xun Xu ◽  
Yashan Zhu ◽  
Kejing Tian ◽  
Tingcan Lin ◽  
Yunyu Li
Keyword(s):  
Basis Function ◽  
Equations Of Motion ◽  
Identification Accuracy ◽  
Problem Solution ◽  
Load Identification ◽  
Random Loads ◽  
Robustness To Noise ◽  
Structure Equations ◽  
Integral Structure ◽  
High Computational Efficiency

Load identification is a very important and challenging indirect load measurement method because load identification is an inverse problem solution with ill-conditioned characteristics. A new method of load identification is proposed here, in which a virtual function was introduced to establish integral structure equations of motion, and partial integration was applied to reduce the response types in the equations. The effects of loading duration, the type of basis function, and the number of basis function expansion items on the calculation efficiency and the accuracy of load identification were comprehensively taken into account. Numerical simulation and experimental results showed that our algorithm could not only effectively identify periodic and random loads, but there was also a trade-off between the calculation efficiency and identification accuracy. Additionally, our algorithm can improve the ill-conditionedness of the solution of load identification equations, has better robustness to noise, and has high computational efficiency.

Research of load identification based on multiple-input multiple-output SVM model selection

2011 ◽  
Vol 226 (5) ◽  
pp. 1395-1409 ◽  
Author(s):  
W Mao ◽  
M Tian ◽  
G Yan
Keyword(s):  
Model Selection ◽  
Multiple Input Multiple Output ◽  
Identification Accuracy ◽  
Support Vector ◽  
Load Identification ◽  
Multi Objective ◽  
Svm Model ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Leave One Out

In this article, the problem of multiple-input multiple-output (MIMO) load identification is addressed. First, load identification is proved in dynamic theory as non-linear MIMO black-box modelling process. Second, considering the effect of hyper-parameters in small-size sample problem, a new MIMO Support Vector Machine (SVM) model selection method based on multi-objective particle swarm optimization is proposed in order to improve the identification's performance. The proposed method treats the model selection of MIMO SVM as a multi-objective optimization problem, and leave-one-out generalization errors of all output models are minimized simultaneously. Once the Pareto-optimal solutions are found, the SVM model with the best generalization ability is determined. The proposed method is evaluated in the experiment of dynamic load identification on cylinder stochastic vibration system, demonstrating its benefits in comparison to the existing model selection methods in terms of identification accuracy and numerical stability, especially near the peaks.

scholarly journals CONSTRUCTION AND RESEARCH OF FULL BALANCE ENERGY OF VARIATIONAL PROBLEM MOTION SURFACE AND GROUNDWATER FLOWS

2017 ◽  
Vol 1 ◽  
pp. 45-52
Author(s):  
Petro Venherskyi
Keyword(s):  
Variational Problem ◽  
Initial Conditions ◽  
Equations Of Motion ◽  
Variational Problems ◽  
Energy System ◽  
Problem Solution ◽  
Flow Energy ◽  
Balance Energy ◽  
Basic Equations ◽  
Surface And Groundwater

Based on the laws of conservation of mass and momentum the basic equations of motion with unknown quantities velocity and piezometric pressure are written. These equations are supplemented with boundary and initial conditions describing the motion of compatible flows. Based on the laws of motion continuum, received conditions contact on the common border interaction of surface and groundwater flows. Variational problems formulated compatible flow. Energy norms of basic components of variational problem are analyzed. Correctness of constructing variational problem arising from construction of the energy system of equations that allow to investigate properties of the problem solution, its uniqueness, stability, dependence on initial data and more. Energy equation of motion of surface and groundwater flows are derived and investigated. It is shown that the total energy compatible flow depends on sources that are located inside the domain or on its border.

Tension Force Estimation of Cables with Two Intermediate Supports

2020 ◽  
Vol 20 (03) ◽  
pp. 2050032
Author(s):  
Banfu Yan ◽  
Wenbing Chen ◽  
You Dong ◽  
Xiaomo Jiang
Keyword(s):  
Flexural Rigidity ◽  
Numerical Models ◽  
Equations Of Motion ◽  
Field Tests ◽  
Identification Accuracy ◽  
Tension Force ◽  
Force Estimation ◽  
Dimensional Parameter ◽  
Force Identification ◽  
Arch Bridges

The presence of intermediate supports usually imposes difficulties in identifying the tension force of stayed cables in cable-stayed bridges or hanger cables in arch bridges. This paper establishes the partial differential equations of motion of the cable and derives two numerical models with (Model 1) and without (Model 2) considering the flexural rigidity. The effects of two intermediate supports on the identification accuracy of the cable tension force are further studied analytically and experimentally. The effects of several non-dimensional parameters (e.g. damper location, support stiffness, flexural rigidity, and mode order of the cable) on the identification accuracy of the models are also investigated. It is theoretically concluded that the simplified Model 2 provides acceptable accuracy on tension force identification when the non-dimensional parameter [Formula: see text] is greater than 90 (slender cables), whereas the accurate Model 1 can be applied for tension force identification at any scenarios. The feasibility of two models is further verified by three numerical examples and field tests on two real-world arch bridges.

Parametric Studies on Moving Axle Load Identification

2001 ◽  
Author(s):  
Ling Yu ◽  
Tommy H. T. Chan
Keyword(s):  
Time Domain ◽  
Time Domain Method ◽  
Identification Accuracy ◽  
Load Identification ◽  
System Parameters ◽  
Domain Method ◽  
Parametric Studies ◽  
The Time Domain ◽  
Value Decomposition ◽  
Pseudo Inverse

Abstract This study addresses the effects of various parameters on moving axle load identification when vehicles move across a bridge. Main emphases are placed on evaluation of two solutions, pseudo-inverse (PI) and Singular value decomposition (SVD) solutions, to an over-determined set of equations established under the time domain method (TDM) and frequency-time domain method (FTDM). The effects of vehicle-bridge system parameters and of measurement system parameters on the TDM and FTDM are also investigated. Assessment results based on experiments in laboratory show that the TDM is a better and non-sensitive method. The SVD technique can effectively improve identification accuracy when using TDM and FTDM particularly in the case of the FTDM.

scholarly journals Free Vibration Study of Anti-Symmetric Angle-Ply Laminated Plates under Clamped Boundary Conditions

2016 ◽  
Vol 3 (1) ◽  
Author(s):  
K.K. Viswanathan ◽  
K. Karthik ◽  
Y.V.S.S. Sanyasiraju ◽  
Z.A. Aziz
Keyword(s):  
Free Vibration ◽  
Boundary Conditions ◽  
Radial Basis Function ◽  
Basis Function ◽  
Equations Of Motion ◽  
Spline Approximation ◽  
Numerical Approach ◽  
Laminated Plates ◽  
Radial Basis ◽  
Plane Displacement

AbstractTwo type of numerical approach namely, Radial Basis Function and Spline approximation, used to analyse the free vibration of anti-symmetric angle-ply laminated plates under clamped boundary conditions. The equations of motion are derived using YNS theory under first order shear deformation. By assuming the solution in separable form, coupled differential equations obtained in term of mid-plane displacement and rotational functions. The coupled differential is then approximated using Spline function and radial basis function to obtain the generalize eigenvalue problem and parametric studies are made to investigate the effect of aspect ratio, length-to-thickness ratio, number of layers, fibre orientation and material properties with respect to the frequency parameter. Some results are compared with the existing literature and other new results are given in tables and graphs.

scholarly journals Augmented Tikhonov Regularization Method for Dynamic Load Identification

2020 ◽  
Vol 10 (18) ◽  
pp. 6348 ◽  
Author(s):  
Jinhui Jiang ◽  
Hongzhi Tang ◽  
M Shadi Mohamed ◽  
Shuyi Luo ◽  
Jianding Chen
Keyword(s):  
Kernel Function ◽  
Tikhonov Regularization ◽  
Regularization Method ◽  
Identification Accuracy ◽  
Tikhonov Regularization Method ◽  
Load Identification ◽  
Structural Dynamic ◽  
Green Kernel ◽  
Ill Posed ◽  
Residual Norm

We introduce the augmented Tikhonov regularization method motivated by Bayesian principle to improve the load identification accuracy in seriously ill-posed problems. Firstly, the Green kernel function of a structural dynamic response is established; then, the unknown external loads are identified. In order to reduce the identification error, the augmented Tikhonov regularization method is combined with the Green kernel function. It should be also noted that we propose a novel algorithm to determine the initial values of the regularization parameters. The initial value is selected by finding a local minimum value of the slope of the residual norm. To verify the effectiveness and the accuracy of the proposed method, three experiments are performed, and then the proposed algorithm is used to reproduce the experimental results numerically. Numerical comparisons with the standard Tikhonov regularization method show the advantages of the proposed method. Furthermore, the presented results show clear advantages when dealing with ill-posedness of the problem.

Study on Dynamic Load Identification with Precision Integration Method

2011 ◽  
Vol 243-249 ◽  
pp. 184-187
Author(s):  
Ling Ling Jia ◽  
Li Bing Jin ◽  
Yang Han
Keyword(s):  
Discrete Time ◽  
Integration Method ◽  
Dynamic Loads ◽  
Load Identification ◽  
Precise Integration ◽  
Numerical Examples ◽  
Precise Integration Method ◽  
Random Loads ◽  
Ice Loads ◽  
External Loads

Based on the principle of precise integration method, for DOF and MDOF system, it is supposed that external loads are in linear regular within small discrete time. In further, a identification method of dynamic loads are proposed. And two real ice loads are used to study the new method. The results of numerical examples indicate that the precise integration method, with better steady and capability of resisting noise, are applicable for both steady or random loads. Otherwise, it can save more time for calculation and can be applied in real engineering.

scholarly journals A Load Identification Application Technology Based on Regularization Method and Finite Element Modified Model

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Bingrong Miao ◽  
Feng Zhou ◽  
Chuanying Jiang ◽  
Yaoxiang Luo ◽  
Hui Chen
Keyword(s):  
Finite Element ◽  
Estimation Error ◽  
Element Model ◽  
Identification Accuracy ◽  
Load Identification ◽  
Noise Levels ◽  
Application Technology ◽  
Modified Model ◽  
Ill Posed ◽  
Good Agreement

An improved load identification technology of a beam based on different regularization methods and model modifying methods is presented in an attempt to minimize the estimation error at several periodic loads. A hybrid model is developed to simulate such ill-posed problem interactions under different noise levels. The finite element model is modified with the different optimization algorithms to obtain the equivalent constraint condition. Experimental verification is also carried out to obtain correct modes and frequencies by considered vibration response and different boundary conditions. The measured results demonstrate the good agreement with the identification results. The results are shown that the improved method not only has more adaptive range and higher identification accuracy but also has effective identification ability for loads under different noise levels.

Vibration Load Identification of Offshore Platforms Based on Neural Network

2009 ◽  
Author(s):  
Rujian Ma ◽  
Guixi Li ◽  
Jianshan Lin
Keyword(s):  
Neural Network ◽  
Element Model ◽  
Training Data ◽  
Identification Accuracy ◽  
Offshore Platforms ◽  
Load Identification ◽  
Vibration Load ◽  
The Neural Network ◽  
Production Platform ◽  
Set Up

The vibration load identification was performed in this paper, where the neural network is introduced in order to overcome the disadvantages of the commonly used method. The first step is to establish a finite element model of the platform using ANSYS software. The training data of neural network is obtained by applying simulation to get response at the identification point of the model. The neural network model of the platform is then set up. The network is trained until the convergence state by using the above data. Finally, the vibration load identification for W12-1 oil production platform is performed using the method, where the measured response data are inputted to the trained network and the identification loads of the platform are obtained. The results indicate that there are more advantages of the method as compared with commonly used load identification method when used for such large and complex structures as offshore platforms and the identification accuracy of the method is satisfactory.

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