Identification of Compliant Contact Force Parameters in Multibody Systems Based on the Neural Network Approach Related to Municipal Property Damages

Gholamhossein Lari; Saeed Ebrahimi

doi:doi:10.11648/j.ajnna.20170305.11

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Identification of Compliant Contact Force Parameters in Multibody Systems Based on the Neural Network Approach Related to Municipal Property Damages

Gholamhossein Lari, Saeed Ebrahimi

Published in American Journal of Neural Networks and Applications (Volume 3, Issue 5)

Received: 14 November 2017 Accepted: 14 December 2017 Published: 8 January 2018

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Abstract

In this paper, a new approach for identification of the compliant contact parameters model in multibody systems simulation using a neural network algorithm is presented. Based on the training and testing the network for some input and output data sets, a general framework is established for identification of these parameters. For this purpose, first, the literature devoted to the identification of contact parameters using analytical approaches and methods based on the neural network is reviewed in brief. Next, the proposed approach is outlined. Finally, considering a classical example of contact of two bodies, the proposed approach is applied for verification of the obtained results.

Published in	American Journal of Neural Networks and Applications (Volume 3, Issue 5)
DOI	10.11648/j.ajnna.20170305.11
Page(s)	49-55
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2018. Published by Science Publishing Group

Keywords

Compliant Contact Force Model, Multibody Systems, Stiffness and Damping Coefficients, Neural Network

References

[1]	P. Wriggers. Computational Contact Mechanics. John Wiley & Sons, Chichester, 2002.
[2]	H. M. Lankarani and P. E. Nikravesh. Continuous Contact Force Models for Impact Analysis in Multibody Systems. Nonlinear Dynamics, 5, 193 207, 1994.
[3]	K. L. Johnson. Contact Mechanics. Cambridge University Press, Cambridge, 1985.
[4]	Y. A. Khulief and A. A. Shabana. A Continuous Force Model for the Impact Analysis of Flexible Multibody Systems. Mechanism and Machine Theory, 22, 213 224, 1987.
[5]	H. M. Lankarani and P. E. Nikravesh. A Contact Force Model with Hysteresis Damping for Impact Analysis of Multibody Systems. ASME Journal of Mechanical Design, 112, 369 376, 1990.
[6]	J. M. P. Dias and M. S. Pereira. Dynamics of Flexible Mechanical Systems with Contact-Impact and Plastic Deformations. Nonlinear Dynamics, 8, 491 512, 1995.
[7]	K. H. Hunt and F. R. E. Grossley. Coefficient of Restitution Interpreted as Damping in Vibroimpact. ASME Journal of Applied Mechanics, 97, 440 445, 1975.
[8]	M. Weber, K. Patel, O. Ma, and I. Sharf. Identification of Contact Dynamics Model Parameters from Constrained Robotic Operations. Journal of Dynamic Systems, Transactions ASME, 128, 307-318, 2006.
[9]	S. T. Venkataraman, S. Gulati, J. Barhen and N. Toomarian. A Neural Network Based Identification of Environments Models for Compliant Control of Space Robots. IEEE Transactions On Robotics And Automation, 9, 685-697, 1993.
[10]	O. zsahin, H. N. zgü ven and E. Budak. Estimation of Dynamic Contact Parameters For Machine Tool Spindle-Holder-Tool Assemblies Using Artificial Neural Networks. Proceedings of the 3rd International Conference on Manufacturing Engineering (ICMEN), 1-3 October, Chalkidiki, Greece, 2008.
[11]	F. Sharifi. Collision Modeling, Simulation and Identification of Robotic Manipulators Interacting with Enviroments. Journal of intelligent and robotic systems, 13, 1-44, 1995.
[12]	F. Pfeiffer and C. Glocker. Multibody Dynamics with Unilateral Contacts. John Wiley & Sons, NewYork, 1996.

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APA Style

Gholamhossein Lari, Saeed Ebrahimi. (2018). Identification of Compliant Contact Force Parameters in Multibody Systems Based on the Neural Network Approach Related to Municipal Property Damages. American Journal of Neural Networks and Applications, 3(5), 49-55. https://doi.org/10.11648/j.ajnna.20170305.11

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ACS Style

Gholamhossein Lari; Saeed Ebrahimi. Identification of Compliant Contact Force Parameters in Multibody Systems Based on the Neural Network Approach Related to Municipal Property Damages. Am. J. Neural Netw. Appl. 2018, 3(5), 49-55. doi: 10.11648/j.ajnna.20170305.11

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AMA Style

Gholamhossein Lari, Saeed Ebrahimi. Identification of Compliant Contact Force Parameters in Multibody Systems Based on the Neural Network Approach Related to Municipal Property Damages. Am J Neural Netw Appl. 2018;3(5):49-55. doi: 10.11648/j.ajnna.20170305.11

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@article{10.11648/j.ajnna.20170305.11,
  author = {Gholamhossein Lari and Saeed Ebrahimi},
  title = {Identification of Compliant Contact Force Parameters in Multibody Systems Based on the Neural Network Approach Related to Municipal Property Damages},
  journal = {American Journal of Neural Networks and Applications},
  volume = {3},
  number = {5},
  pages = {49-55},
  doi = {10.11648/j.ajnna.20170305.11},
  url = {https://doi.org/10.11648/j.ajnna.20170305.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajnna.20170305.11},
  abstract = {In this paper, a new approach for identification of the compliant contact parameters model in multibody systems simulation using a neural network algorithm is presented. Based on the training and testing the network for some input and output data sets, a general framework is established for identification of these parameters. For this purpose, first, the literature devoted to the identification of contact parameters using analytical approaches and methods based on the neural network is reviewed in brief. Next, the proposed approach is outlined. Finally, considering a classical example of contact of two bodies, the proposed approach is applied for verification of the obtained results.},
 year = {2018}
}

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TY  - JOUR
T1  - Identification of Compliant Contact Force Parameters in Multibody Systems Based on the Neural Network Approach Related to Municipal Property Damages
AU  - Gholamhossein Lari
AU  - Saeed Ebrahimi
Y1  - 2018/01/08
PY  - 2018
N1  - https://doi.org/10.11648/j.ajnna.20170305.11
DO  - 10.11648/j.ajnna.20170305.11
T2  - American Journal of Neural Networks and Applications
JF  - American Journal of Neural Networks and Applications
JO  - American Journal of Neural Networks and Applications
SP  - 49
EP  - 55
PB  - Science Publishing Group
SN  - 2469-7419
UR  - https://doi.org/10.11648/j.ajnna.20170305.11
AB  - In this paper, a new approach for identification of the compliant contact parameters model in multibody systems simulation using a neural network algorithm is presented. Based on the training and testing the network for some input and output data sets, a general framework is established for identification of these parameters. For this purpose, first, the literature devoted to the identification of contact parameters using analytical approaches and methods based on the neural network is reviewed in brief. Next, the proposed approach is outlined. Finally, considering a classical example of contact of two bodies, the proposed approach is applied for verification of the obtained results.
VL  - 3
IS  - 5
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Author Information

Gholamhossein Lari

Safety and Fire Fighting Organization, Shiraz Municipality, Shiraz, Iran
Saeed Ebrahimi

Department of Mechanical Engineering, Yazd University, Yazd, Iran

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APA Style

Gholamhossein Lari, Saeed Ebrahimi. (2018). Identification of Compliant Contact Force Parameters in Multibody Systems Based on the Neural Network Approach Related to Municipal Property Damages. American Journal of Neural Networks and Applications, 3(5), 49-55. https://doi.org/10.11648/j.ajnna.20170305.11

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ACS Style

Gholamhossein Lari; Saeed Ebrahimi. Identification of Compliant Contact Force Parameters in Multibody Systems Based on the Neural Network Approach Related to Municipal Property Damages. Am. J. Neural Netw. Appl. 2018, 3(5), 49-55. doi: 10.11648/j.ajnna.20170305.11

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AMA Style

Gholamhossein Lari, Saeed Ebrahimi. Identification of Compliant Contact Force Parameters in Multibody Systems Based on the Neural Network Approach Related to Municipal Property Damages. Am J Neural Netw Appl. 2018;3(5):49-55. doi: 10.11648/j.ajnna.20170305.11

Copy | Download

@article{10.11648/j.ajnna.20170305.11,
  author = {Gholamhossein Lari and Saeed Ebrahimi},
  title = {Identification of Compliant Contact Force Parameters in Multibody Systems Based on the Neural Network Approach Related to Municipal Property Damages},
  journal = {American Journal of Neural Networks and Applications},
  volume = {3},
  number = {5},
  pages = {49-55},
  doi = {10.11648/j.ajnna.20170305.11},
  url = {https://doi.org/10.11648/j.ajnna.20170305.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajnna.20170305.11},
  abstract = {In this paper, a new approach for identification of the compliant contact parameters model in multibody systems simulation using a neural network algorithm is presented. Based on the training and testing the network for some input and output data sets, a general framework is established for identification of these parameters. For this purpose, first, the literature devoted to the identification of contact parameters using analytical approaches and methods based on the neural network is reviewed in brief. Next, the proposed approach is outlined. Finally, considering a classical example of contact of two bodies, the proposed approach is applied for verification of the obtained results.},
 year = {2018}
}

Copy | Download

TY  - JOUR
T1  - Identification of Compliant Contact Force Parameters in Multibody Systems Based on the Neural Network Approach Related to Municipal Property Damages
AU  - Gholamhossein Lari
AU  - Saeed Ebrahimi
Y1  - 2018/01/08
PY  - 2018
N1  - https://doi.org/10.11648/j.ajnna.20170305.11
DO  - 10.11648/j.ajnna.20170305.11
T2  - American Journal of Neural Networks and Applications
JF  - American Journal of Neural Networks and Applications
JO  - American Journal of Neural Networks and Applications
SP  - 49
EP  - 55
PB  - Science Publishing Group
SN  - 2469-7419
UR  - https://doi.org/10.11648/j.ajnna.20170305.11
AB  - In this paper, a new approach for identification of the compliant contact parameters model in multibody systems simulation using a neural network algorithm is presented. Based on the training and testing the network for some input and output data sets, a general framework is established for identification of these parameters. For this purpose, first, the literature devoted to the identification of contact parameters using analytical approaches and methods based on the neural network is reviewed in brief. Next, the proposed approach is outlined. Finally, considering a classical example of contact of two bodies, the proposed approach is applied for verification of the obtained results.
VL  - 3
IS  - 5
ER  -

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