TY  - JOUR
AB  - 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.
VL  - 36
IS  - 6
SN  - 0264-4401
DO  - 10.1108/EC-09-2018-0410
UR  - https://doi.org/10.1108/EC-09-2018-0410
AU  - Lu Xiaohong
AU  - Wang Yongquan
AU  - Li Jie
AU  - Zhou Yang
AU  - Ren Zongjin
AU  - Liang Steven Y.
PY  - 2019
Y1  - 2019/01/01
TI  - Three-dimensional coordinate measurement algorithm by optimizing BP neural network based on GA
T2  - Engineering Computations
PB  - Emerald Publishing Limited
SP  - 2066
EP  - 2083
Y2  - 2024/04/24
ER  -