A preliminary feasibility study of a short-term prognosis of mining towers tops’ displacements with the use of artificial neural networks

• Authors: Marek Dudzik , Dawid Łątka , Michał Repelewicz , Edward Stewarski , Anna Stręk
• Languages of publication: PL

Abstracts

PL

Mining industry is a key sector of many national economies, thus even a small crack in a mining site echoes nationwide. This strategic sector is subjected to special safety care in every aspect, including operational safety of engineering structures. The newest technologies are employed to diagnose and monitor the working structures and buildings. In this article we propose an innovative idea of combining GPS monitoring system with artificial neural network prognosing to build a prediction tool for displacement of mining shafts in operational conditions. The paper describes a training of a neural network system whose task is to prognose the displacements of the top of a mine shaft tower in direction in a selected period of time. The data used for the training come from the GPS monitoring of displacements of the top of the S 1.2 mining shaft tower. The tower is located in the mining works LW “Bogdanka”.

Keywords

PL

artificial neural network, artificial neural network training, displacement of the top of mining shaft tower, GPS monitoring

• Publisher: [unknown2]
• Journal: Czasopismo Techniczne
• Year: -

Dates

online

2015-04-16

Contributors

author

Marek Dudzik

author

Dawid Łątka

author

Michał Repelewicz

author

Edward Stewarski

author

Anna Stręk