Study on condition monitoring of power-shift steering transmission based on support vector machine

Ying Feng Zhang; Biao Ma; Yuan Zhu; Jin Le Zhang

doi:10.1109/CISE.2009.5364068

Study on condition monitoring of power-shift steering transmission based on support vector machine

Ying Feng Zhang^*, Biao Ma, Yuan Zhu, Jin Le Zhang

^*Corresponding author for this work

School of Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper is aimed at the condition monitoring problem of the Power-shift Steering Transmission (PSST), a method of multiple out least squares support vector regression is developed which is applied to prediction of spectrometric oil analysis data. Radial Basis Function (RBF) is used is this algorithm. There are two parameters γ and σ². The selection of γ and σ² is studied using cross validation method with spectrometric oil analysis data. The prediction of spectrometric oil analysis data for PSST is done. A comparative analysis is made between predictive and actual values. The method has been proved that it has better accuracy in prediction, and any possible problem in PSST can be found through a comparative analysis which has important significance for preventing faults.

Original language	English
Title of host publication	Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009
DOIs	https://doi.org/10.1109/CISE.2009.5364068
Publication status	Published - 2009
Event	2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009 - Wuhan, China Duration: 11 Dec 2009 → 13 Dec 2009

Publication series

Name	Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009

Conference

Conference	2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009
Country/Territory	China
City	Wuhan
Period	11/12/09 → 13/12/09

Keywords

Condition monitoring
Power-Shift Steering Transmission (PSST)
Support Vector Machine (SVM)

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10.1109/CISE.2009.5364068

Cite this

Zhang, Y. F., Ma, B., Zhu, Y., & Zhang, J. L. (2009). Study on condition monitoring of power-shift steering transmission based on support vector machine. In Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009 Article 5364068 (Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009). https://doi.org/10.1109/CISE.2009.5364068

Zhang, Ying Feng ; Ma, Biao ; Zhu, Yuan et al. / Study on condition monitoring of power-shift steering transmission based on support vector machine. Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009. 2009. (Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009).

@inproceedings{483c26e6d51f4436877f4d1d954fdbd1,

title = "Study on condition monitoring of power-shift steering transmission based on support vector machine",

abstract = "This paper is aimed at the condition monitoring problem of the Power-shift Steering Transmission (PSST), a method of multiple out least squares support vector regression is developed which is applied to prediction of spectrometric oil analysis data. Radial Basis Function (RBF) is used is this algorithm. There are two parameters γ and σ2. The selection of γ and σ2 is studied using cross validation method with spectrometric oil analysis data. The prediction of spectrometric oil analysis data for PSST is done. A comparative analysis is made between predictive and actual values. The method has been proved that it has better accuracy in prediction, and any possible problem in PSST can be found through a comparative analysis which has important significance for preventing faults.",

keywords = "Condition monitoring, Power-Shift Steering Transmission (PSST), Support Vector Machine (SVM)",

author = "Zhang, {Ying Feng} and Biao Ma and Yuan Zhu and Zhang, {Jin Le}",

year = "2009",

doi = "10.1109/CISE.2009.5364068",

language = "English",

isbn = "9781424445073",

series = "Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009",

booktitle = "Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009",

note = "2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009 ; Conference date: 11-12-2009 Through 13-12-2009",

}

Zhang, YF, Ma, B, Zhu, Y & Zhang, JL 2009, Study on condition monitoring of power-shift steering transmission based on support vector machine. in Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009., 5364068, Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009, 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009, Wuhan, China, 11/12/09. https://doi.org/10.1109/CISE.2009.5364068

Study on condition monitoring of power-shift steering transmission based on support vector machine. / Zhang, Ying Feng; Ma, Biao; Zhu, Yuan et al.
Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009. 2009. 5364068 (Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Study on condition monitoring of power-shift steering transmission based on support vector machine

AU - Zhang, Ying Feng

AU - Ma, Biao

AU - Zhu, Yuan

AU - Zhang, Jin Le

PY - 2009

Y1 - 2009

N2 - This paper is aimed at the condition monitoring problem of the Power-shift Steering Transmission (PSST), a method of multiple out least squares support vector regression is developed which is applied to prediction of spectrometric oil analysis data. Radial Basis Function (RBF) is used is this algorithm. There are two parameters γ and σ2. The selection of γ and σ2 is studied using cross validation method with spectrometric oil analysis data. The prediction of spectrometric oil analysis data for PSST is done. A comparative analysis is made between predictive and actual values. The method has been proved that it has better accuracy in prediction, and any possible problem in PSST can be found through a comparative analysis which has important significance for preventing faults.

AB - This paper is aimed at the condition monitoring problem of the Power-shift Steering Transmission (PSST), a method of multiple out least squares support vector regression is developed which is applied to prediction of spectrometric oil analysis data. Radial Basis Function (RBF) is used is this algorithm. There are two parameters γ and σ2. The selection of γ and σ2 is studied using cross validation method with spectrometric oil analysis data. The prediction of spectrometric oil analysis data for PSST is done. A comparative analysis is made between predictive and actual values. The method has been proved that it has better accuracy in prediction, and any possible problem in PSST can be found through a comparative analysis which has important significance for preventing faults.

KW - Condition monitoring

KW - Power-Shift Steering Transmission (PSST)

KW - Support Vector Machine (SVM)

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DO - 10.1109/CISE.2009.5364068

M3 - Conference contribution

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SN - 9781424445073

T3 - Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009

BT - Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009

T2 - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009

Y2 - 11 December 2009 through 13 December 2009

ER -

Zhang YF, Ma B, Zhu Y, Zhang JL. Study on condition monitoring of power-shift steering transmission based on support vector machine. In Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009. 2009. 5364068. (Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009). doi: 10.1109/CISE.2009.5364068

Study on condition monitoring of power-shift steering transmission based on support vector machine

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