Numerically Trained Ultrasound AI for Monitoring Tool Degradation
نویسندگان
چکیده
Monitoring tool degradation during manufacturing can ensure product accuracy and reliability. However, due to variations in conditions complexity signal analysis, effective broadly applicable monitoring is still challenging achieve. Herein, a novel method using ultrasound signals augmented with numerically trained machine learning technique reported monitor the wear condition of friction stir welding processing tools. Ultrasonic travel axially inside tools, even minor will change time amplitude reflected signal. An artificial intelligence (AI) algorithm selected as suitable referee identify small based on signals. To properly train AI referee, human-error-free data bank numerical simulation generated. The models experimental high fidelity provide comparable As result, model recognize from real experiments subwavelength prediction worn amount pins.
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ژورنال
عنوان ژورنال: Advanced intelligent systems
سال: 2022
ISSN: ['2640-4567']
DOI: https://doi.org/10.1002/aisy.202100215