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Condition-based monitoring for underground mobile machines

Author

Listed:
  • Arto Laukka
  • Juhamatti Saari
  • Jari Ruuska
  • Esko Juuso
  • Sulo Lahdelma

Abstract

Condition-based maintenance (CBM) can significantly reduce maintenance costs by identifying upcoming needs but requires data fusion and more real-time measurements. Typical measurement variables are vibration, temperature, different speeds and pressures. The project aims to develop a solution framework for combining condition monitoring (CM) and process data to integrate CBM with control and timing of the maintenance actions. The use of on-line and periodic CM measurements requires advanced signal processing and feature extraction. This paper focuses on implementing the measurement system in a case study conducted in Pyhäsalmi mine with Sandvik load haul dump (LHD) machinery. The measurement monitoring system was installed on LHD front axle, which is among the most critical parts in LHD machines. A feasible solution was found in the harsh underground conditions. The working stages can be identified from the signals and the measurements are suitable for the development of the condition and stress indices.

Suggested Citation

  • Arto Laukka & Juhamatti Saari & Jari Ruuska & Esko Juuso & Sulo Lahdelma, 2016. "Condition-based monitoring for underground mobile machines," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 23(1), pages 74-89.
    • Handle: RePEc:ids:ijisen:v:23:y:2016:i:1:p:74-89
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    Cited by:

    1. Aleksandra Grzesiek & Radosław Zimroz & Paweł Śliwiński & Norbert Gomolla & Agnieszka Wyłomańska, 2021. "A Method for Structure Breaking Point Detection in Engine Oil Pressure Data," Energies, MDPI, vol. 14(17), pages 1-24, September.
    2. Saari, Juhamatti & Odelius, Johan, 2018. "Detecting operation regimes using unsupervised clustering with infected group labelling to improve machine diagnostics and prognostics," Operations Research Perspectives, Elsevier, vol. 5(C), pages 232-244.

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