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Three-dimensional coordinate measurement algorithm by optimizing BP neural network based on GA

Xiaohong Lu (Key Laboratory for Precision and Non-traditional Machining Technology of Ministry of Education, Dalian University of Technology, Dalian, China)
Yongquan Wang (Key Laboratory for Precision and Non-traditional Machining Technology of Ministry of Education, Dalian University of Technology, Dalian, China)
Jie Li (Key Laboratory for Precision and Non-traditional Machining Technology of Ministry of Education, Dalian University of Technology, Dalian, China)
Yang Zhou (Key Laboratory for Precision and Non-traditional Machining Technology of Ministry of Education, Dalian University of Technology, Dalian, China)
Zongjin Ren (Key Laboratory for Precision and Non-traditional Machining Technology of Ministry of Education, Dalian University of Technology, Dalian, China)
Steven Y. Liang (Georgia Institute of Technology, Atlanta, Georgia, USA)

Engineering Computations

ISSN: 0264-4401

Article publication date: 15 August 2019

Issue publication date: 15 August 2019

Abstract

Purpose

The purpose of this paper is to solve the problem that the analytic solution model of spatial three-dimensional coordinate measuring system based on dual-position sensitive detector (PSD) is complex and its precision is not high.

Design/methodology/approach

A new three-dimensional coordinate measurement algorithm by optimizing back propagation (BP) neural network based on genetic algorithm (GA) is proposed. The mapping relation between three-dimensional coordinates of space points in the world coordinate system and light spot coordinates formed on dual-PSD has been built and applied to the prediction of three-dimensional coordinates of space points.

Findings

The average measurement error of three-dimensional coordinates of space points at three-dimensional coordinate measuring system based on dual-PSD based on GA-BP neural network is relatively small. This method does not require considering the lens distortion and the non-linearity of PSD. It has simple structure and high precision and is suitable for three-dimensional coordinate measurement of space points.

Originality/value

A new three-dimensional coordinate measurement algorithm by optimizing BP neural network based on GA is proposed to predict three-dimensional coordinates of space points formed on three-dimensional coordinate measuring system based on dual-PSD.

Keywords

Acknowledgements

The research is supported by the National Natural Science Foundation of China under Grant Number 51875080. The financial contribution is gratefully acknowledged.

Citation

Lu, X., Wang, Y., Li, J., Zhou, Y., Ren, Z. and Liang, S.Y. (2019), "Three-dimensional coordinate measurement algorithm by optimizing BP neural network based on GA", Engineering Computations, Vol. 36 No. 6, pp. 2066-2083. https://doi.org/10.1108/EC-09-2018-0410

Publisher

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Emerald Publishing Limited

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