[Data Science Use Case] Fault Prediction Detection in Wind Power Generation Facilities

Preventing non-operational hours caused by malfunctions in advance! A case of developing AI to detect signs of failure.

We will introduce a case where fault prediction detection was realized in wind power generation facilities. When a wind turbine experiences a failure, unplanned downtime occurs. By detecting signs of failure, we aimed to improve the efficiency of maintenance and inspections and enhance the operational efficiency of wind turbines. To address this, we developed an AI to detect failure signs from operational sensing data. This resulted in reduced operational costs through more efficient maintenance and inspection work, as well as improved operational rates by preventing unexpected accidents. 【Case Overview】 ■Industry: Social Infrastructure ■Business: Operations and Maintenance ■Challenge: Improvement of Inspection Efficiency ■Analytics and AI Solution - Determine abnormal conditions when deviating from a steady state - Predict whether equipment in an abnormal state will fail subsequently *For more details, please refer to the PDF document or feel free to contact us. - Related link - https://www.tdse.jp/case-study/fault-detection/

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