Prediction of Yarn Quality by Support Vector Machine

Ru Quan Zhang; Jian Qiang Li; Yu He; Hui Jiang

doi:10.4028/www.scientific.net/AMR.503-504.1429

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 503-504Prediction of Yarn Quality by Support Vector...

Prediction of Yarn Quality by Support Vector Machine

Abstract:

For the prediction of yarn quality, this paper presents method to predict the quality of the spinning by a support vector machine. The input parameters to support vector machines including density of coarse yarn, roving twist factor, yarn linear density, yarn twist factor , the output variable is the CV values of spinning, breaking strength, establishment prediction model of CV values, breaking strength SVM. The results showed that: 11 groups of training samples randomly selected from 13 groups samples, two groups as predict sample, forecast errors are below 5% with high accuracy. This research provides a new approach for the spinning process design and quality control.

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Periodical:

Advanced Materials Research (Volumes 503-504)

Pages:

1429-1432

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.503-504.1429

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Online since:

April 2012

Authors:

Ru Quan Zhang, Jian Qiang Li, Yu He, Hui Jiang

Keywords:

Breaking Strength, Evenness CV Value, Predictive Model, Yarn Quality Prediction

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