Conveners
New & Innovative Accelerator Technology
- Mario DI CASTRO (CERN)
Description
Innovation in automation and robotics is an area of focus for increasing efficiency and productivity in the accelerator community.
• How is the accelerator industry utilizing both "off the shelf" and "in house" technologies for handling repetitive tasks to reducing stress and increasing safety for the workforce?
• How are we using Big Data analytics to discover useful, otherwise hidden, patterns to incorporate data-driven decisions for facilities and applying machine learning techniques to model, explore and implement data driven solutions?
• What type sensors are available (pressure, vibration, thermal, etc.). Uses of case scenario will be very greatly appreciated.
A Digital Twin is a dynamic, bespoke model of a physical system, providing real-time information on the asset instant state and allowing for data extrapolation and predictive modelling.
The application of Digital Twins can open a new chapter in the engineering of particle accelerators and their systems. With Digital Twin, data acquisition and asset modelling can be augmented in space and in...
The fast beam interlock system (FBIS) for the ESS accelerator was developed and built in-house by the safety critical systems (SKS) group at the Zurich University of Applied Sciences (ZHAW), in close collaboration with the ESS machine protection (MPS) group. The FBIS plays an essential role in ESS machine protection and is the logic solver element of most protection functions. In order to...
An alarm management system is an essential tool for control room operators to facilitate a fast and effective response to abnormal operating conditions. A major challenge for operators is alarm fatigue resulting from too many concurrent alarms, frequent alarm state changes (nuisance alarms), or recurrence of known bad alarm states that are already handled. We have sought to create a...
The anomalies in the High Voltage Converter Modulator (HVCM) remain a major down time for the Spallation Neutron Source (SNS) facility. To improve the reliability of the HVCMs, several studies using machine learning techniques were to predict faults ahead of time in the SNS accelerator using a single modulator. In this study, we present a multi-module framework based on Conditional Variational...
