Design of a Fiber Alignment Coupling System Based on Spiral Scanning and the DAS SPGD Algorithm

Fig. 7. Iterative curves for each variable under different perturbation amplitudes. (a) Evaluation function value; (b) change of evaluation function value

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Fig. 8. Iterative curves for each variable under different ratios of gain to disturbance. (a) Evaluation function value; (b) change of evaluation function value

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Fig. 9. Iteration curves for each variable of different algorithms. (a) Evaluation function value; (b) change of evaluation function value

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Fig. 10. Distribution of convergence iterative steps of different algorithms

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Fig. 11. Variation in convergence success rates of different algorithms with radial migration

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Fig. 12. Iteration curves for each variable of DAS SPGD under different radial offset ranges. (a) Evaluation function value; (b) change of evaluation function value

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Table 1. Configuration parameters of hardware platform

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Table 1. Configuration parameters of hardware platform

Instrument	Model number	Core parameters	Communication method
Stepper motor	Suruga DS102 Stepper Motor	Minimum precision is 0.5 μm； coordinate setting range is ±99999999 pls	RS232CC
Laser	Yenista Optics Tunics T100S-HP Tunable Laser	Absolute wavelength accuracy is ±20 pm； wavelength range is 1260‒1360 nm； output power is >10 mW （+10 dBm）（tunable）	RS-232C， GPIB
Optical power meter	FH01000-S30PRO	Wavelength range is 850‒1650 nm； measurement range is -40 dBm to 10 dBm； measurement accuracy is ±0.2 dB	USB serial， bluetooth， ethernet

Table 2. Variation in average value and variance of convergence iteration step with perturbation amplitude
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Table 2. Variation in average value and variance of convergence iteration step with perturbation amplitude
Perturbation amplitude Average iteration Variance
1 17.96 171.53
3 7.39 26.19
5 5.42 18.47
7 4.60 14.63
9 7.56 47.40
11 — —

Table 3. Variation in average value and variance of convergence iteration step with ratio of gain to disturbance
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Table 3. Variation in average value and variance of convergence iteration step with ratio of gain to disturbance
Ratio of gain to disturbance Average iteration Variance
0.25 6.58 20.36
0.50 5.33 17.58
1.00 4.78 12.86
1.50 5.37 17.14
2.00 5.93 19.71

Table 4. Parameters setting of different algorithms
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Table 4. Parameters setting of different algorithms
Algorithm Parameters
SPGD $γ = 6$ ， $δ_{u} = 3$
Exp SPGD y=5， a=0， $δ_{u} = 1$
DAS SPGD $C_{1} = 6$ ， $C_{2} = 1$ ， $δ_{u} = 1$

Table 5. Average value and variance of convergent iterative steps for different algorithms
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Table 5. Average value and variance of convergent iterative steps for different algorithms
Parameter DAS SPGD Exp SPGD SPGD
Median iteration 4.00 5.00 5.00
Average iteration 4.81 5.60 7.47
Variance 15.84 21.09 58.61
First quartile 2.00 2.00 2.00
Third quartile 7.00 8.00 10.00
Inter quartile range 5.00 6.00 8.00

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Yanfeng Zhang, Baozhe Chen, He Gu, Hongchuan Cui, Lizhu Hong, Xinwei Li, Zhiyong Li. Design of a Fiber Alignment Coupling System Based on Spiral Scanning and the DAS SPGD Algorithm[J]. Laser & Optoelectronics Progress, 2025, 62(5): 0506008

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Paper Information

Category: Fiber Optics and Optical Communications

Received: May. 20, 2024

Accepted: Aug. 29, 2024

Published Online: Feb. 20, 2025

The Author Email:

DOI:10.3788/LOP241319

CSTR:32186.14.LOP241319

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. Configuration parameters of hardware platform

Table 1. Configuration parameters of hardware platform

Table 2. Variation in average value and variance of convergence iteration step with perturbation amplitude

Table 2. Variation in average value and variance of convergence iteration step with perturbation amplitude

Table 3. Variation in average value and variance of convergence iteration step with ratio of gain to disturbance

Table 3. Variation in average value and variance of convergence iteration step with ratio of gain to disturbance

Table 4. Parameters setting of different algorithms

Table 4. Parameters setting of different algorithms

Table 5. Average value and variance of convergent iterative steps for different algorithms

Table 5. Average value and variance of convergent iterative steps for different algorithms