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This research focus on improving diagnostic methods for low-profile wind turbines, which, due to their characteristics or price, do not justify the addition of a sensor array for monitoring. Therefore, the possibility of training an artificial intelligence AI system for wind turbine diagnosis is investigated. Unlike other research, this study focuses on developing a low-profile, cost-effective AI expert diagnostic system. The process involves training various AIs to verify their ability to detect faults in wind turbines, using a virtual wind turbine model for the database samples.

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Development an Artificial Intelligence Diagnostic System for Low-Profile Wind Turbine Equipment

  • 会议论文

  • 发表日期：

    2025年

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  • Carla Terron-Santiago,
  • Ruben Puche-Panadero,
  • Jordi Burriel-Valencia,
  • Manuel Pineda-Sanchez

摘要

This research focus on improving diagnostic methods for low-profile wind turbines, which, due to their characteristics or price, do not justify the addition of a sensor array for monitoring. Therefore, the possibility of training an artificial intelligence AI system for wind turbine diagnosis is investigated. Unlike other research, this study focuses on developing a low-profile, cost-effective AI expert diagnostic system. The process involves training various AIs to verify their ability to detect faults in wind turbines, using a virtual wind turbine model for the database samples.