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

Preventing non-operational time due to failures in advance! A case of developing AI to detect signs of failure.

We would like to introduce a case where the detection of failure precursors in wind power generation facilities has been realized. When a wind turbine experiences a failure, unplanned downtime occurs. By detecting the precursors to failures, we aimed to improve the efficiency of maintenance and inspections and enhance the operational efficiency of wind turbines. To address this, we developed AI to detect failure signs from operational status sensing data. This resulted in reduced operational costs through improved efficiency of maintenance and inspection tasks, as well as increased operational rates by preventing unexpected accidents. 【Case Overview】 ■Industry: Social Infrastructure ■Business: Operations and Maintenance ■Challenge: Improvement of Inspection Efficiency ■Analytics and AI Solution - Determination of abnormal conditions when deviating from a steady state - Prediction of whether the 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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