| Autor: |
Max Åstrand, Erik Jakobsson, Martin Lindfors, John Svensson |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
International Journal of Mining Science and Technology, Vol 30, Iss 3, Pp 405-411 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
2095-2686 |
| DOI: |
10.1016/j.ijmst.2020.04.006 |
| Popis: |
Poor road conditions in underground mine tunnels can lead to decreased production efficiency and increased wear on production vehicles. A prototype system for road condition monitoring is presented in this paper to counteract this. The system consists of three components i.e. localization, road monitoring, and scheduling. The localization of vehicles is performed using a Rao-Blackwellized extended particle filter, combining vehicle mounted sensors with signal strengths of WiFi access points. Two methods for road monitoring are described: a Kalman filter used together with a model of the vehicle suspension system, and a relative condition measure based on the power spectral density. Lastly, a method for taking automatic action on an ill-conditioned road segment is proposed in the form of a rescheduling algorithm. The scheduling algorithm is based on the large neighborhood search and is used to integrate road service activities in the short-term production schedule while minimizing introduced production disturbances. The system is demonstrated on experimental data collected in a Swedish underground mine. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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