ICALEPCS2023 - List of Keywords (extraction)

Paper	Title	Other Keywords	Page
TUPDP035	New Developments for eGiga2m Historic Database Web Visualizer	database, controls, status, factory	588
	L. Zambon, R. Passuello Elettra-Sincrotrone Trieste S.C.p.A., Basovizza, Italy
	eGiga is an historic database web visualizer since 2002. At the beginning it was connected to a proprietary database schema, support for other schemas was added later, for example HDB and HDB++. eGiga was deeply refactored in 2015 becoming eGiga2m. Between 2022 and 2023 a few improvements have been made, among them, optimization of large data extraction, improvement of images and pdf exports, substitution of 3d chart library with a touch screen enabled one; the addition of: logger status info, a new canvas responsive chart library, adjustable splitter, support for TimescaleDB and HDF5 data format, correlations and time series analysis, and ARIMA (autoregressive integrated moving average) forecast.
	Poster TUPDP035 [0.821 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUPDP035
About •	Received ※ 05 October 2023 — Revised ※ 11 October 2023 — Accepted ※ 14 December 2023 — Issued ※ 17 December 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUPDP099	Spark Activity Monitoring for LHC Beam Dump System	high-voltage, operation, GUI, controls	784
	C.B. Durmus, E. Carlier, N. Magnin, T.D. Mottram, V. Senaj CERN, Meyrin, Switzerland
	LHC Beam Dump System is composed of 25 fast-pulsed magnets per beam to extract and dilute the beam onto an external absorber block. Each magnet is powered by a high voltage generator to discharge the energy stored in capacitors into the magnet by using high voltage switches. These switches are housed in air in cabinets which are not dust protected. In the past years of LHC operation, we noticed electrical sparks on the high voltage switch due to the release of accumulated charges on the surfaces of the insulators and the switches. These sparks can potentially cause self-trigger of the generators increasing the risk of asynchronous dumps which should be avoided as much as possible. In order to detect dangerous spark activity in the generators before a self-trigger occurs, a Spark Activity Monitoring (SAM) system was developed. SAM consists of 50 detection and acquisition systems deployed at the level of each high voltage generator, and one external global surveillance process. The detection and acquisition systems are based on digitisers to detect and capture spark waveforms coming from current pick-ups placed in various electrical paths inside each generator. The global surveillance process is collecting data from all the acquisition systems in order to assess the risk of self-trigger based on the detected sparks amplitude and rate. This paper describes the architecture, implementation, optimisation, deployment and operational experience of the SAM system.
	Poster TUPDP099 [1.334 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUPDP099
About •	Received ※ 06 October 2023 — Revised ※ 21 October 2023 — Accepted ※ 05 December 2023 — Issued ※ 09 December 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THMBCMO01	New Developements on HDB++, the High-performance Data Archiving for Tango Controls	TANGO, database, controls, interface	1190
	D. Lacoste, R. Bourtembourg ESRF, Grenoble, France J. Forsberg MAX IV Laboratory, Lund University, Lund, Sweden T. Juerges SKAO, Macclesfield, United Kingdom J.J.D. Mol ASTRON, Dwingeloo, The Netherlands L. Pivetta, G. Scalamera Elettra-Sincrotrone Trieste S.C.p.A., Basovizza, Italy S. Rubio-Manrique ALBA-CELLS, Cerdanyola del Vallès, Spain
	The Tango HDB++ project is a high performance event-driven archiving system which stores data with micro-second resolution timestamps. HDB++ supports many different backends, including MySQL/MariaDB, TimeScaleDB (a time-series PostgreSQL extension), and soon SQLite. Building on its flexible design, latest developments made supporting new backends even easier. HDB++ keeps improving with new features such as batch insertion and by becoming easier to install or setup in a testing environment, using ready to use docker images and striving to simplify all the steps of deployment. The HDB++ project is not only a data storage installation, but a full ecosystem to manage data, query it, and get the information needed. In this effort a lot of tools were developed to put a powerful backend to its proper use and be able to get the best out of the stored data. In this paper we will present as well the latest developments in data extraction, from low level libraries to web viewer integration such as grafana. Pointing out strategies in use in terms of data decimation, compression and others to help deliver data as fast as possible.
	Slides THMBCMO01 [0.926 MB]
	Poster THMBCMO01 [0.726 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THMBCMO01
About •	Received ※ 05 October 2023 — Revised ※ 24 October 2023 — Accepted ※ 08 December 2023 — Issued ※ 16 December 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THSDSC05	The SKAO Engineering Data Archive: From Basic Design to Prototype Deployments in Kubernetes	software, controls, TANGO, database	1590
	T. Juerges SKAO, Macclesfield, United Kingdom A. Dange Tata Consultancy Services, Pune, India
	During its construction and production life cycles, the Square Kilometre Array Observatory (SKAO) will generate non-scientific, i.e. engineering, data. The sources of the engineering data are either hardware devices or software programs that generate this data. Thanks to the Tango Controls software framework, the engineering data can be automatically stored in a relational database, which SKAP refers to as the Engineering Data Archive (EDA). Making the data in the EDA accessible and available to engineers and users in the observatory is as important as storing the data itself. Possible use cases for the data are verification of systems under test, performance evaluation of systems under test, predictive maintenance and general performance monitoring over time. Therefore we tried to build on the knowledge that other research facilities in the Tango Controls collaboration already gained, when they designed, implemented, deployed and ran their engineering data archives. SKAO implemented a prototype for its EDA, that leverages several open-source software packages, with Tango Controls’ HDB++, the Timescaledb time series database and Kubernetes at its core. In this overview we will answer the immediate question "But why do we not just do, what others are doing?" and explain the reasoning behind our choices in the design and in the implementation.
	Poster THSDSC05 [3.062 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THSDSC05
About •	Received ※ 05 October 2023 — Revised ※ 27 October 2023 — Accepted ※ 05 December 2023 — Issued ※ 11 December 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Other Keywords

Page

TUPDP035

New Developments for eGiga2m Historic Database Web Visualizer

database, controls, status, factory

588

L. Zambon, R. Passuello
Elettra-Sincrotrone Trieste S.C.p.A., Basovizza, Italy

eGiga is an historic database web visualizer since 2002. At the beginning it was connected to a proprietary database schema, support for other schemas was added later, for example HDB and HDB++. eGiga was deeply refactored in 2015 becoming eGiga2m. Between 2022 and 2023 a few improvements have been made, among them, optimization of large data extraction, improvement of images and pdf exports, substitution of 3d chart library with a touch screen enabled one; the addition of: logger status info, a new canvas responsive chart library, adjustable splitter, support for TimescaleDB and HDF5 data format, correlations and time series analysis, and ARIMA (autoregressive integrated moving average) forecast.

Poster TUPDP035 [0.821 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUPDP035

About •

Received ※ 05 October 2023 — Revised ※ 11 October 2023 — Accepted ※ 14 December 2023 — Issued ※ 17 December 2023

Cite •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUPDP099

Spark Activity Monitoring for LHC Beam Dump System

high-voltage, operation, GUI, controls

784

C.B. Durmus, E. Carlier, N. Magnin, T.D. Mottram, V. Senaj
CERN, Meyrin, Switzerland

LHC Beam Dump System is composed of 25 fast-pulsed magnets per beam to extract and dilute the beam onto an external absorber block. Each magnet is powered by a high voltage generator to discharge the energy stored in capacitors into the magnet by using high voltage switches. These switches are housed in air in cabinets which are not dust protected. In the past years of LHC operation, we noticed electrical sparks on the high voltage switch due to the release of accumulated charges on the surfaces of the insulators and the switches. These sparks can potentially cause self-trigger of the generators increasing the risk of asynchronous dumps which should be avoided as much as possible. In order to detect dangerous spark activity in the generators before a self-trigger occurs, a Spark Activity Monitoring (SAM) system was developed. SAM consists of 50 detection and acquisition systems deployed at the level of each high voltage generator, and one external global surveillance process. The detection and acquisition systems are based on digitisers to detect and capture spark waveforms coming from current pick-ups placed in various electrical paths inside each generator. The global surveillance process is collecting data from all the acquisition systems in order to assess the risk of self-trigger based on the detected sparks amplitude and rate. This paper describes the architecture, implementation, optimisation, deployment and operational experience of the SAM system.

Poster TUPDP099 [1.334 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUPDP099

About •

Received ※ 06 October 2023 — Revised ※ 21 October 2023 — Accepted ※ 05 December 2023 — Issued ※ 09 December 2023

Cite •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THMBCMO01

New Developements on HDB++, the High-performance Data Archiving for Tango Controls

TANGO, database, controls, interface

1190

D. Lacoste, R. Bourtembourg
ESRF, Grenoble, France
J. Forsberg
MAX IV Laboratory, Lund University, Lund, Sweden
T. Juerges
SKAO, Macclesfield, United Kingdom
J.J.D. Mol
ASTRON, Dwingeloo, The Netherlands
L. Pivetta, G. Scalamera
Elettra-Sincrotrone Trieste S.C.p.A., Basovizza, Italy
S. Rubio-Manrique
ALBA-CELLS, Cerdanyola del Vallès, Spain

The Tango HDB++ project is a high performance event-driven archiving system which stores data with micro-second resolution timestamps. HDB++ supports many different backends, including MySQL/MariaDB, TimeScaleDB (a time-series PostgreSQL extension), and soon SQLite. Building on its flexible design, latest developments made supporting new backends even easier. HDB++ keeps improving with new features such as batch insertion and by becoming easier to install or setup in a testing environment, using ready to use docker images and striving to simplify all the steps of deployment. The HDB++ project is not only a data storage installation, but a full ecosystem to manage data, query it, and get the information needed. In this effort a lot of tools were developed to put a powerful backend to its proper use and be able to get the best out of the stored data. In this paper we will present as well the latest developments in data extraction, from low level libraries to web viewer integration such as grafana. Pointing out strategies in use in terms of data decimation, compression and others to help deliver data as fast as possible.

Slides THMBCMO01 [0.926 MB]

Poster THMBCMO01 [0.726 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THMBCMO01

About •

Received ※ 05 October 2023 — Revised ※ 24 October 2023 — Accepted ※ 08 December 2023 — Issued ※ 16 December 2023

Cite •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THSDSC05

The SKAO Engineering Data Archive: From Basic Design to Prototype Deployments in Kubernetes

software, controls, TANGO, database

1590

T. Juerges
SKAO, Macclesfield, United Kingdom
A. Dange
Tata Consultancy Services, Pune, India

During its construction and production life cycles, the Square Kilometre Array Observatory (SKAO) will generate non-scientific, i.e. engineering, data. The sources of the engineering data are either hardware devices or software programs that generate this data. Thanks to the Tango Controls software framework, the engineering data can be automatically stored in a relational database, which SKAP refers to as the Engineering Data Archive (EDA). Making the data in the EDA accessible and available to engineers and users in the observatory is as important as storing the data itself. Possible use cases for the data are verification of systems under test, performance evaluation of systems under test, predictive maintenance and general performance monitoring over time. Therefore we tried to build on the knowledge that other research facilities in the Tango Controls collaboration already gained, when they designed, implemented, deployed and ran their engineering data archives. SKAO implemented a prototype for its EDA, that leverages several open-source software packages, with Tango Controls’ HDB++, the Timescaledb time series database and Kubernetes at its core. In this overview we will answer the immediate question "But why do we not just do, what others are doing?" and explain the reasoning behind our choices in the design and in the implementation.

Poster THSDSC05 [3.062 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THSDSC05

About •

Received ※ 05 October 2023 — Revised ※ 27 October 2023 — Accepted ※ 05 December 2023 — Issued ※ 11 December 2023

Cite •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)