Nonlinear error compensation for 2D PSD based on SSA-BP neural network

Loujie Zhang; Chunlian Zhan; Dengfeng Dong; Han Gao; Peisong Zhou

doi:10.1117/12.3030719

3 June 2024 Nonlinear error compensation for 2D PSD based on SSA-BP neural network

Loujie Zhang, Chunlian Zhan, Dengfeng Dong, Han Gao, Peisong Zhou

Proceedings Volume 13182, 2024 International Conference on Optoelectronic Information and Optical Engineering (OIOE 2024); 1318224 (2024) https://doi.org/10.1117/12.3030719
Event: 2024 International Conference on Optoelectronic Information and Optical Engineering (OIOE 2024), 2024, Kunming, China

Abstract

The nonlinear errors of Position Sensitive Detectors (PSD) will cause the less tracking accuracy of the laser trackers. To address the issue, in this paper we proposed a nonlinear compensation method, combining Sparrow Search Algorithm (SSA) with BP neural network. The SSA was employed to find optimal initial thresholds and weights of the BP neural network. An SSA-BP neural network model was created and tested using 443 sets of experimental data. The experimental results show that this method reduces the peak error of the BP neural network by over 7 times and lowers the average error by more than 2 times, significantly enhancing the measurement accuracy of the detector.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Loujie Zhang, Chunlian Zhan, Dengfeng Dong, Han Gao, and Peisong Zhou "Nonlinear error compensation for 2D PSD based on SSA-BP neural network", Proc. SPIE 13182, 2024 International Conference on Optoelectronic Information and Optical Engineering (OIOE 2024), 1318224 (3 June 2024); https://doi.org/10.1117/12.3030719

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