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Simulación de resultados de interferometría de moteado para mediciones mejoradas y detección automatizada de defectos
Optics express
|December 19, 2025
Resumen
Este estudio simula la interferometría de moteado para superar desafíos de configuración y análisis. El objetivo es permitir el reconocimiento automatizado de defectos para mediciones eficientes en producción en serie.
Área de la Ciencia:
- Metrología Óptica
- Ensayos No Destructivos
- Mecánica Computacional
Sus antecedentes:
- La holografía de moteado y la cirografía ofrecen un valioso potencial de medición, pero están infrautilizadas debido a configuraciones complejas y análisis manual.
- El análisis automatizado y la configuración simplificada de parámetros son cruciales para una mayor adopción de las técnicas de metrología óptica.
- Los métodos existentes carecen de la eficiencia requerida para el reconocimiento automatizado de defectos en entornos industriales.
Objetivo del estudio:
- Desarrollar un código de simulación para resultados de interferometría de moteado basado en análisis de elementos finitos (FEA).
- Mejorar la optimización de parámetros de las mediciones de interferometría de moteado.
- Generar conjuntos de datos para el desarrollo de modelos de aprendizaje automático (ML) para la detección automatizada de defectos.
Principales métodos:
- Análisis de Elementos Finitos (FEA) para generar datos de desplazamiento.
- Desarrollo de un código de simulación para modelar patrones de franjas de interferometría de moteado a partir de resultados de FEA.
- Creación de conjuntos de datos sintéticos para entrenar y validar algoritmos de ML.
Principales resultados:
- Simulación exitosa de patrones de franjas de interferometría de moteado.
- Demostración de la mejora de la configuración de parámetros para la precisión de la medición.
- Generación de un conjunto de datos fundamental para el reconocimiento de defectos basado en ML.
Conclusiones:
- La simulación de la interferometría de moteado puede abordar desafíos prácticos en su aplicación.
- La simulación desarrollada ayuda a optimizar los parámetros de medición y a crear datos de entrenamiento.
- Este enfoque facilita el desarrollo de sistemas de reconocimiento automatizado de defectos para uso industrial.
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