Vestas Wind Systems had one patents in big data during Q2 2024. The patent filed by Vestas Wind Systems AS in Q2 2024 describes a method for receiving sensor data from multiple wind turbines to determine health indicators for gearbox and generator subcomponents with varying lead times. These indicators correspond to alerts for current or predicted problems with low, medium, or high severity risk levels. A machine learning model trained on sensor data generates these alerts, which can be displayed in a sortable and filterable list for easy monitoring of turbine components. GlobalData’s report on Vestas Wind Systems gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Vestas Wind Systems had no grants in big data as a theme in Q2 2024.
Recent Patents
Application: Systems and methods for displaying renewable energy asset health risk information (Patent ID: US20240201680A1)
The patent filed by Vestas Wind Systems AS describes a method and system for monitoring the health of gearbox and generator subcomponents in multiple wind turbines. The method involves receiving sensor data from the turbines, determining health indicators for the subcomponents with varying lead times, and generating alerts for current or predicted issues with low, medium, or high severity risk levels. These alerts are generated using a machine learning model trained on historical sensor data. The system displays a list of wind turbines sortable by health indicators and filterable by alerts for the gearbox and generator subcomponents, allowing for efficient monitoring and maintenance of the turbines.
Additionally, the system allows for filtering the list of turbines by specific alerts, displaying detailed information for selected turbines, determining overall health indicators for the gearbox and generator, initiating work orders based on alerts, displaying service events, and providing a cross-sectional outline view of the turbine components. The system also includes features such as displaying wind turbines on a map, analyzing temperature, signals, CMS, and vibration data, and grouping turbines by wind turbine farms. Overall, the method and system outlined in the patent aim to enhance the monitoring and maintenance of wind turbines by providing real-time health indicators and alerts for efficient management of turbine components.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
