Method for testing a material
The method uses a hyperspectral camera system with AI evaluation to assess turbomachine material quality in real-time, addressing the lack of predictive capabilities in existing technologies and improving component reliability and production efficiency.
Patent Information
- Application Number
- PCT/DE2024/100541
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2023-06-22
- Filing Date
- 2024-06-19
- Publication Date
- 2024-12-26
AI Technical Summary
Current methods for monitoring materials in turbomachine component production lack real-time prediction capabilities, as hyperspectral measurement data in its unprocessed form does not provide sufficient conclusions about material quality, leading to potential component failures and increased production costs.
A method involving a hyperspectral camera system that sequentially measures powdered material, using AI-based evaluation to predict metallographic and mechanical properties, allowing for real-time assessment of material suitability and operational reliability, and integrating spectral, angular, and time information to detect deviations such as contamination or particle size issues.
This approach enhances the operational reliability of turbomachine components by reducing scrap during production, optimizing the production process, and ensuring component quality through continuous material testing, thereby reducing time and costs.
Smart Images

Figure DE2024100541_26122024_PF_FP_ABST
Abstract
Citation Information
Patent Citations
Method for determining a concentration of at least one material in a powder for an additive manufacturing process
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