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September 2, 2026Technical Physics

Structured Thermal Representation of a Brushless DC Motor Based on Infrared Image Analysis

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Authors

AZA.V. ZayaraМКМ.Б. Косарич

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Overview

Computational study demonstrates structured thermal mapping of brushless DC motors using infrared image clustering, highlighting improved reliability for drone motor monitoring.

Key Points

  • To develop a structured thermal representation method for brushless DC motors by analyzing infrared thermograms in three-dimensional RGB space.
  • Synthesized computer vision and statistical analysis techniques to evaluate infrared thermograms of brushless DC motors in three-dimensional RGB space.
  • Applied Kernel Density Estimation (KDE) and Mean Shift clustering algorithms to group color patterns from the thermograms.
  • Calculated key color moments based on identified clusters to quantify the thermal state of critical motor zones.
  • Formulated a methodological scheme that decomposes motor components into distinct thermal zones using spatial and color criteria.
  • Extracted compact numerical features through color moment calculations to assess and track the thermal state of engine zones qualitatively and quantitatively.

Cite This Study

Zayara et al. (2026) studied this question.

synapsesocial.com/papers/6a97e237c562ede874ec638ehttps://doi.org/10.1134/s1063784226700556
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