Speaker
Description
Particle accelerators rely on complex control systems for their operation. As accelerators grow in scale and complexity, developing and maintaining effective control systems becomes increasingly challenging. In this presentation, we will explore the potential for applying natural language processing (NLP) techniques to improve accelerator operations by closely examining the use of textual data.
We will present our applications of NLP algorithms to logbook data from DESY and BESSY. Initial results demonstrate feasibility for using NLP to automatically parse log entries, categorize events, detect problems, and surface important information.
However, challenges remain in handling physics terminology, noisy data, and model generalization. This presentation will provide an overview of how natural language processing can be applied to accelerate logbooks in field of accelerator controls.
