AI-Enabled Fusion of Optical and Acoustic Sensors for Enhanced Non-Destructive Material Characterization

This PhD thesis focuses on advancing non-destructive testing methods for enhanced data acquisition and processing in materials and production processes. State-of-the-art optical and acoustic (including ultrasound) sensor technologies will be explored to obtain detailed insights without causing harm to materials. The integration and combination of cutting-edge signal processing and machine learning methods such as Compressive Sensing, Super-Resolution Imaging, and Deep Neural Networks will be crucial in enhancing data extraction and analysis. Acoustic techniques like laser ultrasound and photoacoustics for imaging internal structures will be investigated, while also studying methods to counteract attenuation, thus enhancing spatial resolution. All in all, the goal is to revolutionize the characterization of materials and processes by exploring innovative sensor technologies and advanced signal processing and machine learning methods.