A Model for Predicting the Wear Degree of Electrode Tip

Jin Zhang; Peng Xian Zhang; Xiang Jian Xu

doi:10.4028/www.scientific.net/AMM.574.292

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 574A Model for Predicting the Wear Degree of...

A Model for Predicting the Wear Degree of Electrode Tip

Abstract:

A new method is put forward to predicting the degree of electrode tip wear based on a laser measurement and digital image of the surface joint indentation. First, in order to monitoring the degree of electrode tip wear, the decline altitudes of sphere ΔH that can indicate variation of electrode tip shape are measured by means of the laser measurement system. Second, through the correlation analysis between the parameters S₀, S₁, S, K₁ reflecting digital image characteristic of joint indentation and the decline altitudes of sphere ΔH, S₀, S, K₁ are extracted as characteristic parameters of monitoring electrode tip wear. At last, a model of support vector machine (SVM) for predicting the degree of electrode tip wear is established between the parameters S₀, S, K₁ as the input vector and ΔH as the target vector. Test result shows, the correlation coefficient between model prediction and actual measured values are 0.9907. The prediction model can realize estimating the degree of electrode tip wear.

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Periodical:

Applied Mechanics and Materials (Volume 574)

Pages:

292-297

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.574.292

Citation:

Cite this paper

Online since:

July 2014

Authors:

Jin Zhang*, Peng Xian Zhang, Xiang Jian Xu

Keywords:

Electrode Tip Wear, Prediction Model, Resistance Spot Welding, Support Vector Machine (SVM)

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* - Corresponding Author

References

[1] K C Wu. Electrode indentation criterion for resistance spot welding, J . Welding in the World, 1968, 10(10): 472-478.

Google Scholar

[2] Xuqiang Zhang, Aihui Luo, and Yansong Zhang. Charact eristics of elect rode wear in spot welding of hot galvanized dual-phase high strength steel, J. Transactions of the China Welding Institution, 2006, 27( 9): 108-112. (In Chinese).

Google Scholar

[3] Rujuan Li, Mengsheng Li, and Yang Wang. Effect of spherical radius of spot welding electrode on nugget size, J . Transactions of the China Welding Institution, 2008, 29(6): 105-108. (In Chinese.

Google Scholar

[4] Holliday R, Parker J D, and Williams N T. Relative contribution of electrode tip growth mechanisms in spot welding zinc coated steels, J . Welding in the World, 1994, 37(4): 186-193.

Google Scholar

[5] Lu F, Dong P. Model for estimating electrode face diameter during resistance spot welding, J . Science and technology of welding and jioning, 1999, 14(5): 285-289.

DOI: 10.1179/136217199101537888

Google Scholar

[6] Lu Wang, Jingfeng Qian, and Min Wang. Forecast of electrode life in spot welding of galvanized steel sheet, J . Transactions of the China Welding Institution, 2006, 27(7): 184-192. (In Chinese).

Google Scholar

[7] Shijie Dong, Norman Zhou. Effect of TiC coating on electrode tip surface on electrode degradation during resistance spot welding zinc coated steel, J . The Chinese Journal of Nonferrous Metals, 2005, 15(2): 109-112. (In Chinese).

Google Scholar

[8] Pengxian Zhang, Jianhong Chen, and Wenjiang Du. Quality monitoring of resistance spot welding based on image processing of welding spot surface, J . Transactions of the China Welding Institution, 2006, 27(12): 57-64. (In Chinese).

Google Scholar

[9] Nello C, John S T. An introduction to support vector machines and other kernel-based learning methods. Beijing: Publishing House of Electronics Industry. (2004).

Google Scholar

[10] http: /www. csie. ntu. edu. tw/~cjlin /libsvm.

Google Scholar