Yarn apparent evenness detection based on L0 norm smoothing and the expectation maximization method

Author:

Zhang Huanhuan123ORCID,Zhu Houchun12,Yan Kai12,Jing Junfeng12,Su Zebin12

Affiliation:

1. School of Electronics and Information, Xi’an Polytechnic University, China

2. Branch of Shaanxi Artificial Intelligence Joint Laboratory, Xi’an Polytechnic University, China

3. School of Automation, Northwestern Polytechnical University, China

Abstract

During spinning, knitting and weaving processes, the yarn apparent evenness is an important factor, which determines the quality of subsequent spinning production and fabric performance. This paper presents a powerful method which is based on L0 norm smoothing and the expectation maximization method to detect the yarn apparent evenness. The L0 norm smoothing method is first applied to remove the noise and enhance the yarn apparent evenness diameter features. Then, the expectation maximization method and the morphological opening operation were used to obtain the yarn evenness. Finally, we calculated the yarn apparent evenness diameter and the coefficient of variation of the evenness of the yarn apparent diameter. Compared with the capacitive evenness testers, the Otsu detection method and the fuzzy C-means detection method, our method can accurately detect the yarn apparent evenness better than the selected state-of-the-art methods.

Funder

Shaanxi Provincial Key R&D Program Project

The Shaanxi Provincial College of Science and Technology Youth Talent Support Project

Shaanxi Provincial Department of Education Youth Innovation Team Project

Doctoral Scientific Research Foundation of Xi'an Polytechnic University

Innovation Capability Support Program of Shaanxi

National Natural Science Foundation of China

Publisher

SAGE Publications

Subject

Polymers and Plastics,Chemical Engineering (miscellaneous)

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