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A Method for Structure Breaking Point Detection in Engine Oil Pressure Data

Author

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  • Aleksandra Grzesiek

    (Faculty of Geoengineering, Mining and Geology, Wroclaw University of Science and Technology, Na Grobli 15, 50-421 Wroclaw, Poland)

  • Radosław Zimroz

    (Faculty of Geoengineering, Mining and Geology, Wroclaw University of Science and Technology, Na Grobli 15, 50-421 Wroclaw, Poland)

  • Paweł Śliwiński

    (KGHM Polska Miedź S.A., M. Skłodowskiej-Curie 48, 59-301 Lubin, Poland)

  • Norbert Gomolla

    (DMT GmbH & Co. KG, Am Technologiepark 1, 45307 Essen, Germany)

  • Agnieszka Wyłomańska

    (Faculty of Pure and Applied Mathematics, Hugo Steinhaus Center, Wrocław University of Science and Technology, Wyspiańskiego 27, 50-370 Wrocław, Poland)

Abstract

In this paper, a heavy-duty loader operated in an underground mine is discussed. Due to extremely harsh operational conditions, an important maintenance problem is related to engine oil pressure. We have found that when the degradation process appears, the nature of variation of pressure engine oil changes. Following this observation, we have proposed a data analysis procedure for the structure break point detection. It is based on specific data pre-processing and further statistical analysis. The idea of the paper is to transform the data into a nearly monotonic function that describes the variation of machine condition or in the statistical language—change of the regime inside the process. To achieve that goal we proposed an original data processing procedure. The dataset analyzed in the paper covers one month of observation. We have received confirmation that during that period, maintenance service has been done. The purpose of our research was to remove ambiguity related to direct oil pressure analysis and visualize oil pressure variation in the diagnostic context. As a fleet of machines in the considered company covers more than 1000 loaders/trucks/drilling machines, the importance of this approach is serious from a practical point of view. We believe that it could be also an inspiration for other researchers working with industrial data.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:17:p:5496-:d:628376
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    References listed on IDEAS

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    1. Kucharczyk, Daniel & Wyłomańska, Agnieszka & Zimroz, Radosław, 2017. "Structural break detection method based on the Adaptive Regression Splines technique," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 499-511.
    2. Zhao, Hongshan & Liu, Huihai & Hu, Wenjing & Yan, Xihui, 2018. "Anomaly detection and fault analysis of wind turbine components based on deep learning network," Renewable Energy, Elsevier, vol. 127(C), pages 825-834.
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    7. Yonglong Yan & Jian Li & David Wenzhong Gao, 2014. "Condition Parameter Modeling for Anomaly Detection in Wind Turbines," Energies, MDPI, vol. 7(5), pages 1-17, May.
    8. Sikora, Grzegorz & Wyłomańska, Agnieszka & Krapf, Diego, 2018. "Recurrence statistics for anomalous diffusion regime change detection," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 380-394.
    9. Joanna Janczura, 2014. "Pricing electricity derivatives within a Markov regime-switching model: a risk premium approach," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 79(1), pages 1-30, February.
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    Cited by:

    1. Sergey Zhironkin & Dawid Szurgacz, 2022. "Mining Technologies Innovative Development: Industrial, Environmental and Economic Perspectives," Energies, MDPI, vol. 15(5), pages 1-5, February.
    2. Dawid Szurgacz & Beata Borska & Ryszard Diederichs & Sergey Zhironkin, 2022. "Development of a Hydraulic System for the Automatic Expansion of Powered Roof Support," Energies, MDPI, vol. 15(3), pages 1-15, January.
    3. Dawid Szurgacz & Beata Borska & Sergey Zhironkin & Ryszard Diederichs & Anthony J. S. Spearing, 2022. "Optimization of the Load Capacity System of Powered Roof Support: A Review," Energies, MDPI, vol. 15(16), pages 1-15, August.
    4. Dawid Szurgacz & Beata Borska & Ryszard Diederichs & Anthony J. S. Spearing & Sergey Zhironkin, 2023. "Minimizing Internal Leaks of a Powered Roof Support’s Hydraulic Prop Based on Double Block with Charging," Energies, MDPI, vol. 16(3), pages 1-14, January.

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