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Cluster Computing
Published in: Cluster Computing 2/2019

03-01-2018

A segmentation scheme with SVR-based prediction in stroke-sensing cylinder

Authors: Lu Liu, Yanqing Guo, Yongling Fu, Chuangchuang Li, Liang Guo

Published in: Cluster Computing | Special Issue 2/2019

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Abstract

Signal processing in stroke-sensing system of cylinder has been addressed by researchers from very different fields. However, the low accuracy of subdividing technique results in the difficulties in signal segmentation. This paper proposes methodology analyzes the measuring principle and subdivision error of the displacement detection. A segmentation scheme based on support vector regression (SVR) algorithm is developed to efficiently compensate the complexity and nonlinearity in tangent subdivision, and it enables accurate modeling and predicting of angle variation by applying SVR algorithm. Further, the regression model improves the accuracy by resolving the segmentation interval. Due to the significances presented in this work, the detection error decreases from 1.59 to 0.286%, when processed with the proposed segmentation algorithm. Experimental results are statistically analyzed, which makes it a promising basis for the realization of exact position detection.
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Metadata
Title
A segmentation scheme with SVR-based prediction in stroke-sensing cylinder
Authors
Lu Liu
Yanqing Guo
Yongling Fu
Chuangchuang Li
Liang Guo
Publication date
03-01-2018
Publisher
Springer US
Published in
Cluster Computing / Issue Special Issue 2/2019
Print ISSN: 1386-7857
Electronic ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-017-1645-2

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