The performance prediction of roadheader using Artificial neural network

سال انتشار: 1401
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 34

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شناسه ملی سند علمی:

MMMC04_028

تاریخ نمایه سازی: 16 آبان 1401

چکیده مقاله:

Roadheaders are one of those machines that have a unique ability and flexibility in mechanical excavating of soft to moderate rock formations, therefore they are widely used in underground mining and tunneling. Evaluating and predicting the performance of hydraulic is considered a very important factor in their successful application. The main goal of this research is to provide a model for predicting the amount of ICR based on the characteristics of the excavated rock formations. Artificial neural network method is used. The database was then analyzed through ANN to yield an optimum predictive model for ICR (m۳/h). Results showed that there is a close relation between actual (measured) data and predicted data with coefficient of determination (R۲) of ۰.۸۵ and root mean square error (RMSE) =۰.۰۷.

نویسندگان

Alireza Afradi

Department of Mining and Geology, Qaemshahr Branch, Islamic Azad University, Qaemshahr, Iran

Mohammad Raei Abbas Abadi

Department of Mining Engineering,Savadkooh Branch, Islamic Azad University, Savadkooh, Iran

Gheys Habibi mahali

Department of Mining and Geology, Qaemshahr Branch, Islamic Azad University, Qaemshahr, Iran