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FORMULATION OF THE MACHINE LEARNING PROBLEM FOR THE INTEGRITY OF MINING EQUIPMENT MONITORING

Toichkin N. A.  (candidate of technical sciences, associate professor, department of informatics and computer engineering, Murmansk Arctic university, Apatity, Russia)

Vinogradov N. K.  (Murmansk Arctic university, Apatity, Russia)

The presented project is aimed at creating an information system for monitoring the integrity of mining equipment using machine learning methods. The study proposes a method for creating a synthetic training set by generating raster images of an object with its structure destroyed at different angles and incorporating white noise to simulate unpredictable conditions often present in the mining industry. This will help the model develop reliability and adaptability to various environmental factors that may affect the integrity of the equipment. By generating raster images of objects with varying degrees of structural failure from different angles, the model will learn to identify and analyze the integrity of mining equipment in real time. The project's goal is to transform the monitoring and control of mining equipment using advanced machine learning techniques, improving efficiency, productivity and safety in the industry.

Keywords:Machine learning, model, neural network, mining equipment, information system, training set.
 

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Citation link:
Toichkin N. A., Vinogradov N. K. FORMULATION OF THE MACHINE LEARNING PROBLEM FOR THE INTEGRITY OF MINING EQUIPMENT MONITORING // Современная наука: актуальные проблемы теории и практики. Серия: Естественные и Технические Науки. -2024. -№04. -С. 109-112 DOI 10.37882/2223-2966.2024.04.31
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