Baker Hughes had 17 patents in artificial intelligence during Q1 2024. Baker Hughes Co filed patents in Q1 2024 for systems and methods related to earth-boring tool wear monitoring, additive manufacturing process optimization, corrosion detection in industrial assets using machine learning, BHA design optimization, and predicting downhole measurement data. These innovations involve utilizing artificial intelligence, numerical optimization algorithms, and predictive modeling to improve efficiency and accuracy in various industrial processes. GlobalData’s report on Baker Hughes gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Baker Hughes grant share with artificial intelligence as a theme is 23% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: System for obtaining a physics-guided bit wear model and related methods (Patent ID: US20240102362A1)
The patent filed by Baker Hughes Co. describes an earth-boring tool system that utilizes sensors to monitor wear on drilling tools. The system receives wear data, generates physics-based dull grading labels, and trains an artificial intelligence model to predict tool wear based on labeled data and physics-based models. The system aims to improve tool maintenance and replacement by providing warnings to operators when replacement is needed, based on the AI model's predictions.
The system's method involves receiving wear data, obtaining labeled dull grading data, generating physics-based dull grading labels, and training an AI model to predict tool wear. The method also includes applying weights to the data, verifying the AI model with historical wear data, and generating physics-based wear models. By utilizing drilling parameters and historical data, the system aims to accurately predict tool wear and provide timely warnings to operators for efficient maintenance and replacement of drilling tools.
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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.
