Artificial neural network assisted laser chip collimator assembly and impact on multi-emitter module beam parameter product

Hao Yu; Giammarco Rossi; Andrea Braglia; Guido Perrone

doi:10.1117/12.2254031

22 February 2017 Artificial neural network assisted laser chip collimator assembly and impact on multi-emitter module beam parameter product

Hao Yu, Giammarco Rossi, Andrea Braglia, Guido Perrone

Author Affiliations +

Proceedings Volume 10085, Components and Packaging for Laser Systems III; 1008508 (2017) https://doi.org/10.1117/12.2254031
Event: SPIE LASE, 2017, San Francisco, California, United States

Abstract

A new tool based on artificial neural networks to assist in the accurate positioning of the lenses used to collimate the beams emitted by the individual chips forming multi-emitter diode laser modules is presented. Then, a new expression for the evaluation of the obtained beam quality is disclosed and the impact of different choices on the overall module performance in terms of beam quality and coupling efficiency into a collecting fiber is analyzed. Experimental validations with different combinations of lenses are reported to prove the effectiveness of the proposed approach.

Conference Presentation

Citation Download Citation

Hao Yu, Giammarco Rossi, Andrea Braglia, and Guido Perrone "Artificial neural network assisted laser chip collimator assembly and impact on multi-emitter module beam parameter product", Proc. SPIE 10085, Components and Packaging for Laser Systems III, 1008508 (22 February 2017); https://doi.org/10.1117/12.2254031

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