Project Goal

Our aim is to make control systems used for the LHC more efficient and smarter. We are working to enhance the functionality of WinCC OA (a SCADA tool used widely at CERN) and to apply data analytics techniques to the recorded monitoring data, in order to detect anomalies and systematic issues that may impact upon system operation and maintenance. 

Background

The HL-LHC programme aims to increase the integrated luminosity — and hence the rate of particle collisions — by a factor of ten beyond the LHC’s design value. Monitoring and control systems will therefore become increasingly complex, with unprecedented data throughputs. Consequently, it is vital to further improve the performance of these systems, and to make use of data analytics algorithms to detect anomalies and anticipate future behaviour. Achieving this involves a number of related lines of work. This project focuses on the development of a modular and future-proof archiving system (NextGen Archiver – NGA) that supports different SQL and NOSQL technologies to enable data analytics. It is important that this can be scaled up to meet our requirements beyond 2023.

Progress

In 2023, the team focused on two main topics: preparation for the deployment of the NGA in all WinCC OA systems in ATLAS, LHCb and CMS and development of a backend for TimescaleDB. CERN-wide deployment of the NGA was initially planned for the Long Shutdown 3 (2026 – 2028). However, thanks to the very good experience with using the NGA in more than one hundred systems at the ALICE experiment, a decision to migrate already during Year-End Technical Stop 2023-24 has been taken by ATLAS, LHCb and CMS. The NGA team has supported this undertaking by providing the tools, support and performing database schema upgrades. All the steps of the process have been automated, allowing the interventions to be finished in unprecedentedly short time windows. Based on the results of the performance and functional tests done in 2023, TimescaleDB is considered to be the best candidate to supersede InfluxDB as an alternative to Oracle. Significant progress has also been made on the TimescaleDB backend, paving the way for a preview release for pilot deployments in the first half of 2024

Next Steps

In 2024, the team will focus on implementing some missing features in the Oracle backend and continuing the development of the TimescaleDB backend. The performance of TimescaleDB at the scale of large CERN distributed WinCC OA systems (hundreds of nodes, millions of datapoints, retention policies spanning years) will be evaluated. Additionally, the flexibility of queries will be improved by allowing to better specify the source of the data.

 

Project Coordinator: Rafal Kulaga

Technical Team: Pedro Agostinho, Rafal Kulaga, Antonin Kveton, Ewald Sperrer

Siemens ETM Collaboration Liaisons: Pedro Agostinho, Ewald Sperrer, Christopher Stoegerer

In partnership with: Siemens