Aprovechamiento de la Minería de Datos para una Mejora en la Predicción de Desprendimientos de Carbón y Gas en Operaciones Mineras
Palabras clave:
seguridad minera, modelado predictivo, evaluación de riesgosResumen
La seguridad en la producción minera se ve significativamente comprometida por accidentes de desprendimientos de carbón y gas. Con el fin de mejorar la precisión científica en la predicción de los riesgos de desprendimientos de carbón y gas, se desarrolló un software de sistema (V1.2.0) utilizando la arquitectura cliente/servidor, el lenguaje de programación Visual Basic y la base de datos SQL Server 2000. Se emplearon el método de control estadístico de procesos (SPC, por sus siglas en inglés) y análisis de regresión logística para evaluar y establecer el valor crítico de riesgo de desprendimiento para índices individuales, como el valor S de los recortes de perforación y el valor K1 del índice de desorción. A través de un análisis multivariado de acoplamiento de información, se exploró la interrelación de las alertas de desprendimientos, lo que condujo a la derivación de la ecuación de predicción de riesgo de desprendimiento. Posteriormente, se aplicaron los métodos de control estadístico de procesos y regresión logística a minas típicas. Los resultados demostraron la determinación precisa de los valores de sensibilidad para cada profundidad de perforación utilizando el método SPC, con una tasa de precisión del 94.7% lograda mediante el método de regresión logística. Estas metodologías demuestran ser valiosas para la detección oportuna de peligros de desprendimientos durante las operaciones mineras.
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