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A general methodology for simulation model validation and model updating of the coordination mechanism with uncertainty

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Abstract

In order to improve the accuracy and credibility of the dynamic simulation model of the coordination mechanism, a general simulation model validation and updating framework was proposed. First, the dynamic model of the coordination mechanism was established considering two friction models. Then, in order to validate the accuracy of the simulation model, for the high-dimensional uncertainty, a validation method of the coordination simulation model based on principal component analysis-area index was proposed. Aiming at the problem that the simulation model was unreliable, a simulation model updating method based on parameter identification was proposed. Finally, the correctness and effectiveness of the method were verified, and the result showed that the accuracy of the simulation updating model with identified LuGre friction model was improved by 31.03 % than the one with identified Coulomb friction model. Thus, the accuracy and credibility of the coordination mechanism simulation model were greatly improved. It provides a theoretical support for the simulation model validation & updating of the coordination mechanism and other mechanical mechanisms.

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Abbreviations

M :

The mass of the coordination arm

A 1 :

The areas of the cylinder piston without rod cavity

A 2 :

The areas of the cylinder piston with rod cavity

p 1 :

The pressures of the cylinder piston without rod cavity

p 2 :

The pressures of the cylinder piston with rod cavity

F t :

Tangential friction

F n :

Normal positive pressure

c f :

Sliding friction coefficient

c d :

Dynamic correction coefficient

v t :

Relative tangential velocity

z(t):

The average elastic deformation of bristles

v s :

The StriBeck velocity

F s :

The maximum static friction

λ 0 :

The stiffness coefficient of bristles

λ 1 :

The damping coefficient of bristles

λ 2 :

The viscosity coefficient of bristles

F f(t):

The LuGre friction force

q :

The relative displacement

\({{\boldsymbol{\dot q}}}\) :

The relative velocity

\({{\boldsymbol{\ddot q}}}\) :

The relative acceleration

M(q,t):

The mass matrix

C(q,q,t):

The generalized damping matrix

Q :

The external force matrix

F s(y):

The CDF of the simulation prediction model

S t(y):

The ECDF of the experimental data

d(F s, S t):

Minkowski-L1 distance

Σ :

The covariance matrix

p k :

The principal component

c k :

The contribution rate

α :

The set of parameters to be identified of the coordination model

x(t i):

The value of the simulated displacement

X(t i):

The value of the tested displacement

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Acknowledgments

This work is supported by Scientific Research Foundation for High-level Talents of Nanjing Institute of Technology (grant number YKJ202104), China. The authors also gratefully thank the editors and reviewers of this manuscript.

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Authors and Affiliations

  1. School of Mechanical Engineering, Nanjing Institute of Technology, Nanjing, 211167, China

    Taisu Liu & Yuyang Niu

  2. School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China

    Guangsong Chen

Authors
  1. Taisu Liu
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  2. Yuyang Niu
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  3. Guangsong Chen
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Corresponding author

Correspondence to Taisu Liu.

Additional information

T. S. Liu works at the Nanjing Institute of Technology. He received his Ph.D. in the School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, P. R. China. His current research interests include simulation model validation & model updating, robust optimization design, data driven, machine learning and digital twins.

Y. Y. Niu is an undergraduate of the Nanjing Institute of Technology, Nanjing, P. R. China. His current research interests include simulation modeling, model validation & model updating, mechanism control.

G. S. Chen is a Professor of the Nanjing University of Science and Technology. He received his Ph.D. in the School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, P. R. China. His current research interests include simulation model validation & model updating, finite element analysis, fault diagnosis, machine learning and digital twins.

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Liu, T., Niu, Y. & Chen, G. A general methodology for simulation model validation and model updating of the coordination mechanism with uncertainty. J Mech Sci Technol 37, 6271–6286 (2023). https://doi.org/10.1007/s12206-023-1105-2

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  • DOI: https://doi.org/10.1007/s12206-023-1105-2

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