MMM Identifying Damage for Recycled Pumping Rod Base on SVM

Hai Yan Xing; Ya Tong Han; Ping Qin; Chang Hai Liu

doi:10.4028/www.scientific.net/AMM.401-403.1251

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 401-403MMM Identifying Damage for Recycled Pumping Rod...

MMM Identifying Damage for Recycled Pumping Rod Base on SVM

Abstract:

Remanufacturing is an important way to develop recycling economy. However, the quality reliability testing is a bottleneck for the recycled product. Metal Magnetic Memory (MMM) technology is a valid method for early damage testing based on the magneto-mechanical effect. This paper aims at quantitative identifying damage for the recycled pumping rod（RPR）. The MMM rules of RPR damage are found through fatigue experiments. By using four-dimensional MMM parameter vectors, that is, peek-peek value，differential gradient，integral gradient and energy, are marked the damages. Furthermore，a multi-level damage classification model has been established base on optimal multi-classification algorithm of support vector machine (SVM) for RPR. The relationship is given between the damage degrees and MMM signals, which provides a theoretical basis and engineering tool of RPR reliability evaluation.

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Periodical:

Applied Mechanics and Materials (Volumes 401-403)

Pages:

1251-1254

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.401-403.1251

Citation:

Cite this paper

Online since:

September 2013

Authors:

Hai Yan Xing, Ya Tong Han, Ping Qin, Chang Hai Liu

Keywords:

Identifying Damage, Metal Magnetic Memory, Recycled Pumping Rod, Support Vector Machine (SVM)

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