Conveners
Anomaly Detection / Failure Prediction: Anomaly Detection & Failure Prediction 1
- Annika Eichler (Deutschles Elektronen Synchrotron DESY)
- Annika Eichler (DESY)
- Jason St. John (Fermilab)
The successful operation of the laser-based synchronization system of the European X-Ray Free Electron Laser relies on the precise functioning of numerous dynamic components operating within closed loops with controllers. This study presents a comprehensive overview of the application of data-driven machine learning methods to detect and classify disturbances in these dynamic systems,...
NSLS-II has been working with SLAC and Argonne on ML applications for improving accelerator reliability; specifically in predicting preventable (slow) trips & in using anomaly detection to identify most likely trip-causes to reduce recovery time. We are several years into the project, and already have positive results in the ‘trip prevention’ application.
Beam diagnostic technology is one of the foundations of large particle accelerator facilities. A challenge with operating these systems is the measurement of beam dynamics. Many methods such as beam position monitors have an inherent destructive quality to the beam and produce perturbations after the measurement. The ability to measure the beam conditions with non-destructive edge radiation...
Within the context of the European X-Ray Free-Electron Laser (EuXFEL), where 800 superconducting radio-frequency cavities (SRFCs) are employed to accelerate electron bunches to energies as high as 17.5 GeV, ensuring safe and optimal accelerator operation is crucial. In this work, we introduce a machine learning (ML)-enhanced approach for detecting anomalies, with a particular focus on...
The Linac Condition Anomaly Prediction Emergence Project (L-CAPE) at Fermilab National Accelerator Lab (FNAL) seeks to apply data-analytic methods to improve the information available to MCR Operators and to automate the task of labeling Linac outage types as they occur by recognizing patterns in real-time machine data. Predicting outages in a credible manner could provide useful information...
