研究目的
To develop an improved optimization approach using Taguchi and genetic algorithms for designing high transmission optical filters with specific performance requirements.
研究成果
The integrated Taguchi and genetic algorithm approach successfully optimizes the design parameters for a high transmission optical filter, achieving 99.22% transmittance at 550 nm with 24 layers. This method significantly reduces the number of required experiments from 27 to 9, cutting computation time by approximately two-thirds while maintaining design accuracy. It demonstrates robustness and efficiency, making it suitable for similar optimization problems in optical filter design and potentially other domains.
研究不足
The method relies on computational simulations and may not account for practical fabrication constraints such as the difficulty in depositing very thin layers (e.g., less than 10 nm). The genetic algorithm parameters (e.g., mutation rate, population size) are fixed and could be further optimized. The study is focused on high transmission filters in the visible region and may not generalize to other filter types without adaptation.
1：Experimental Design and Method Selection:
The study integrates the Taguchi method to reduce the number of design experiments and the genetic algorithm to search for optimal design parameters. The Taguchi method uses orthogonal arrays and signal-to-noise ratio to identify the best factor-level combinations, while the genetic algorithm optimizes layer thicknesses based on a merit function comparing desired and calculated transmittance.
2：Sample Selection and Data Sources:
The design specifications include a transmittance of around 99% in the 525-575 nm wavelength range, with no dips, and a total stack thickness less than 2.0 μm. The desired transmittance profile is predefined.
3：0 μm. The desired transmittance profile is predefined.
List of Experimental Equipment and Materials:
3. List of Experimental Equipment and Materials: Materials used include titanium dioxide (refractive index 2.1), tantalum dioxide (2.05), magnesium fluoride (1.38), and silicon dioxide (1.46) for the optical layers. A computer program in MATLAB is used for simulations.
4：1), tantalum dioxide (05), magnesium fluoride (38), and silicon dioxide (46) for the optical layers. A computer program in MATLAB is used for simulations.
Experimental Procedures and Operational Workflow:
4. Experimental Procedures and Operational Workflow: First, Taguchi's L9 orthogonal array is applied to three factors (thickness range, refractive index combination, number of layers) with three levels each, reducing experiments from 27 to 9. For each experiment, the genetic algorithm is run with parameters like population size 100, scattered crossover, mutation rate 0.1, and 1000 iterations to compute transmittance and merit function. The best combination from Taguchi is used in a final genetic algorithm run to obtain optimized thickness values.
5：For each experiment, the genetic algorithm is run with parameters like population size 100, scattered crossover, mutation rate 1, and 1000 iterations to compute transmittance and merit function. The best combination from Taguchi is used in a final genetic algorithm run to obtain optimized thickness values.
Data Analysis Methods:
5. Data Analysis Methods: Transmittance is calculated using matrix multiplication methods for multilayer stacks. The merit function evaluates the difference between desired and calculated transmittance over 51 wavelength points from 400-700 nm. Signal-to-noise ratio from Taguchi analysis helps identify robust parameter settings.
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