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February 19, 2026Mathematics16 citationsOpen Access

Statistical Modeling and Forecasting of Operational Reliability of Induction Motors of Mining Dump Trucks

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APAleksey F. PryalukhinNMNikita MARTYUSHEVBMBoris V. Malozyomov

Key Points

  • The aim is to develop a statistical model to predict the operational reliability of induction motors in dump trucks.
  • Utilized censored data for time to failure and operational efficiency of motors.
  • Applied Weibull and lognormal distributions to assess reliability indicators.
  • Constructed a generalized life curve for the stator and bearing unit.
  • Developed software for calculating distribution parameters and visualizing reliability.
  • Interval estimates for the service life and residual service life were obtained.
  • Software implementation confirmed the approach's effectiveness for diagnosing induction motor performance.
  • The method enhances the maintenance system optimization for heavy equipment.

Abstract

This study presents a statistical modeling approach for predicting the operational reliability of induction motors used in dump truck drives. The proposed method uses censored data, including both time to failure and data on properly operating engines, to assess reliability indicators, such as uptime based on Weibull and lognormal distributions. A generalized “life curve” of the stator and bearing unit is constructed, which makes it possible to determine interval estimates of the service life and residual service life. The model is implemented as software for calculating distribution parameters and visualizing reliability dependencies. Approbation based on the operational data of quarry transport confirmed the applicability of the proposed approach for diagnosing and optimizing the maintenance system of induction motors of heavy equipment.

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Cite This Study

Pryalukhin et al. (2026) studied this question.

synapsesocial.com/papers/6996a887ecb39a600b3ef582https://doi.org/10.3390/math14040706
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