Investigation on Application of Support Vector Machine Algorithm in the Experimental Simulation System for Mechanism Motion Reliability

Zhang Tong; Li Sen; Qiao Jia-dong

doi:doi:10.11648/j.sd.20170501.13

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Investigation on Application of Support Vector Machine Algorithm in the Experimental Simulation System for Mechanism Motion Reliability

Zhang Tong, Li Sen, Qiao Jia-dong

Published in Science Discovery (Volume 5, Issue 1)

Received: 13 March 2017 Published: 15 March 2017

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Abstract

The complexity of the mechanism brings great difficulty to the calculation of the mechanism motion reliability, and the computer simulation algorithm based on Monte Carlo method needs a great number of simulation. The further-development of LMS Virtual. Lab was carried out, and the least square support vector machine algorithm was used to construct the response surface proxy model. The PSO-GA algorithm is used to optimize the parameters and make the least square support vector machine own a better performance. For the coupling of multiple failure modes, the multiple response surfaces are combined to obtain the reliability of the system. The reliability calculation based on support vector machine algorithm is carried out for the crank slider mechanism and the cam swing bar mechanism, and the feasibility and efficiency of the method are verified by the Monte Carlo method.

Published in	Science Discovery (Volume 5, Issue 1)
DOI	10.11648/j.sd.20170501.13
Page(s)	12-18
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), 2017. Published by Science Publishing Group

Keywords

Reliability, Simulation, Support Vector Machine, Response Surface Models

References

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APA Style

Zhang Tong, Li Sen, Qiao Jia-dong. (2017). Investigation on Application of Support Vector Machine Algorithm in the Experimental Simulation System for Mechanism Motion Reliability. Science Discovery, 5(1), 12-18. https://doi.org/10.11648/j.sd.20170501.13

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ACS Style

Zhang Tong; Li Sen; Qiao Jia-dong. Investigation on Application of Support Vector Machine Algorithm in the Experimental Simulation System for Mechanism Motion Reliability. Sci. Discov. 2017, 5(1), 12-18. doi: 10.11648/j.sd.20170501.13

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AMA Style

Zhang Tong, Li Sen, Qiao Jia-dong. Investigation on Application of Support Vector Machine Algorithm in the Experimental Simulation System for Mechanism Motion Reliability. Sci Discov. 2017;5(1):12-18. doi: 10.11648/j.sd.20170501.13

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@article{10.11648/j.sd.20170501.13,
  author = {Zhang Tong and Li Sen and Qiao Jia-dong},
  title = {Investigation on Application of Support Vector Machine Algorithm in the Experimental Simulation System for Mechanism Motion Reliability},
  journal = {Science Discovery},
  volume = {5},
  number = {1},
  pages = {12-18},
  doi = {10.11648/j.sd.20170501.13},
  url = {https://doi.org/10.11648/j.sd.20170501.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sd.20170501.13},
  abstract = {The complexity of the mechanism brings great difficulty to the calculation of the mechanism motion reliability, and the computer simulation algorithm based on Monte Carlo method needs a great number of simulation. The further-development of LMS Virtual. Lab was carried out, and the least square support vector machine algorithm was used to construct the response surface proxy model. The PSO-GA algorithm is used to optimize the parameters and make the least square support vector machine own a better performance. For the coupling of multiple failure modes, the multiple response surfaces are combined to obtain the reliability of the system. The reliability calculation based on support vector machine algorithm is carried out for the crank slider mechanism and the cam swing bar mechanism, and the feasibility and efficiency of the method are verified by the Monte Carlo method.},
 year = {2017}
}

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TY  - JOUR
T1  - Investigation on Application of Support Vector Machine Algorithm in the Experimental Simulation System for Mechanism Motion Reliability
AU  - Zhang Tong
AU  - Li Sen
AU  - Qiao Jia-dong
Y1  - 2017/03/15
PY  - 2017
N1  - https://doi.org/10.11648/j.sd.20170501.13
DO  - 10.11648/j.sd.20170501.13
T2  - Science Discovery
JF  - Science Discovery
JO  - Science Discovery
SP  - 12
EP  - 18
PB  - Science Publishing Group
SN  - 2331-0650
UR  - https://doi.org/10.11648/j.sd.20170501.13
AB  - The complexity of the mechanism brings great difficulty to the calculation of the mechanism motion reliability, and the computer simulation algorithm based on Monte Carlo method needs a great number of simulation. The further-development of LMS Virtual. Lab was carried out, and the least square support vector machine algorithm was used to construct the response surface proxy model. The PSO-GA algorithm is used to optimize the parameters and make the least square support vector machine own a better performance. For the coupling of multiple failure modes, the multiple response surfaces are combined to obtain the reliability of the system. The reliability calculation based on support vector machine algorithm is carried out for the crank slider mechanism and the cam swing bar mechanism, and the feasibility and efficiency of the method are verified by the Monte Carlo method.
VL  - 5
IS  - 1
ER  -

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Author Information

Zhang Tong

School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China
Li Sen

School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China
Qiao Jia-dong

School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China

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APA Style

Zhang Tong, Li Sen, Qiao Jia-dong. (2017). Investigation on Application of Support Vector Machine Algorithm in the Experimental Simulation System for Mechanism Motion Reliability. Science Discovery, 5(1), 12-18. https://doi.org/10.11648/j.sd.20170501.13

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ACS Style

Zhang Tong; Li Sen; Qiao Jia-dong. Investigation on Application of Support Vector Machine Algorithm in the Experimental Simulation System for Mechanism Motion Reliability. Sci. Discov. 2017, 5(1), 12-18. doi: 10.11648/j.sd.20170501.13

Copy | Download

AMA Style

Zhang Tong, Li Sen, Qiao Jia-dong. Investigation on Application of Support Vector Machine Algorithm in the Experimental Simulation System for Mechanism Motion Reliability. Sci Discov. 2017;5(1):12-18. doi: 10.11648/j.sd.20170501.13

Copy | Download

@article{10.11648/j.sd.20170501.13,
  author = {Zhang Tong and Li Sen and Qiao Jia-dong},
  title = {Investigation on Application of Support Vector Machine Algorithm in the Experimental Simulation System for Mechanism Motion Reliability},
  journal = {Science Discovery},
  volume = {5},
  number = {1},
  pages = {12-18},
  doi = {10.11648/j.sd.20170501.13},
  url = {https://doi.org/10.11648/j.sd.20170501.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sd.20170501.13},
  abstract = {The complexity of the mechanism brings great difficulty to the calculation of the mechanism motion reliability, and the computer simulation algorithm based on Monte Carlo method needs a great number of simulation. The further-development of LMS Virtual. Lab was carried out, and the least square support vector machine algorithm was used to construct the response surface proxy model. The PSO-GA algorithm is used to optimize the parameters and make the least square support vector machine own a better performance. For the coupling of multiple failure modes, the multiple response surfaces are combined to obtain the reliability of the system. The reliability calculation based on support vector machine algorithm is carried out for the crank slider mechanism and the cam swing bar mechanism, and the feasibility and efficiency of the method are verified by the Monte Carlo method.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - Investigation on Application of Support Vector Machine Algorithm in the Experimental Simulation System for Mechanism Motion Reliability
AU  - Zhang Tong
AU  - Li Sen
AU  - Qiao Jia-dong
Y1  - 2017/03/15
PY  - 2017
N1  - https://doi.org/10.11648/j.sd.20170501.13
DO  - 10.11648/j.sd.20170501.13
T2  - Science Discovery
JF  - Science Discovery
JO  - Science Discovery
SP  - 12
EP  - 18
PB  - Science Publishing Group
SN  - 2331-0650
UR  - https://doi.org/10.11648/j.sd.20170501.13
AB  - The complexity of the mechanism brings great difficulty to the calculation of the mechanism motion reliability, and the computer simulation algorithm based on Monte Carlo method needs a great number of simulation. The further-development of LMS Virtual. Lab was carried out, and the least square support vector machine algorithm was used to construct the response surface proxy model. The PSO-GA algorithm is used to optimize the parameters and make the least square support vector machine own a better performance. For the coupling of multiple failure modes, the multiple response surfaces are combined to obtain the reliability of the system. The reliability calculation based on support vector machine algorithm is carried out for the crank slider mechanism and the cam swing bar mechanism, and the feasibility and efficiency of the method are verified by the Monte Carlo method.
VL  - 5
IS  - 1
ER  -

Copy | Download