ICALEPCS2021 - List of Keywords (cryomodule)

Paper	Title	Other Keywords	Page
MOPV001	Status of the SARAF-Phase2 Control System	controls, EPICS, LLRF, network	93
	F. Gougnaud, P. Bargueden, G. Desmarchelier, A. Gaget, P. Guiho, A. Lotode, Y. Mariette, V. Nadot, N. Solenne CEA-DRF-IRFU, France D. Darde, G. Ferrand, F. Gohier, T.J. Joannem, G. Monnereau, V. Silva CEA-IRFU, Gif-sur-Yvette, France H. Isakov, A. Perry, E. Reinfeld, I. Shmuely, Y. Solomon, N. Tamim Soreq NRC, Yavne, Israel T. Zchut CEA LIST, Palaiseau, France
	SNRC and CEA collaborate to the upgrade of the SARAF accelerator to 5 mA CW 40 Mev deuteron and proton beams and also closely to the control system. CEA is in charge of the Control System (including cabinets) design and implementation for the Injector (upgrade), MEBT and Super Conducting Linac made up of 4 cryomodules hosting HWR cavities and solenoid packages. This paper gives a detailed presentation of the control system architecture from hardware and EPICS software points of view. The hardware standardization relies on MTCA.4 that is used for LLRF, BPM, BLM and FC controls and on Siemens PLC 1500 series for vacuum, cryogenics and interlock. CEA IRFU EPICS Environment (IEE) platform is used for the whole accelerator. IEE is based on virtual machines and our MTCA.4 solutions and enables us to have homogenous EPICS modules. It also provides a development and production workflow. SNRC has integrated IEE into a new IT network based on advanced technology. The commissioning is planned to start late summer 2021.
	Poster MOPV001 [1.787 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-MOPV001
About •	Received ※ 09 October 2021 Revised ※ 20 October 2021 Accepted ※ 03 November 2021 Issue date ※ 11 March 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUBR04	Control System of Cryomodule Test Facilities for SHINE*	controls, cryogenics, power-supply, monitoring	353
	H.Y. Wang, G.H. Chen, J.F. Chen, J.G. Ding, M. Li, Y.J. Liu, Q.R. Mi, H.F. Miao, C.L. Yu SSRF, Shanghai, People’s Republic of China
	Funding: Work supported by Shanghai Municipal Science and Technology Major Project (Grant No. 2017SHZDZX02) Shanghai HIgh repetition rate XFEL aNd Extreme light facility (SHINE) is under construction. The 8 GeV superconducting Linac consists of seventy-five 1.3 GHz and two 3.9 GHz cryomodules. A cryomodule assembling and test workshop is established. Multiple platforms have been built for cryomodule and superconducting cavity test, including two vertical test platforms, two horizontal test platform, one multiple test platform and one liquid helium visualization platform. The local control systems are all based on Yokogawa PLC, which monitor and control the process variables such as temperature, pressure, liquid level and power of the heater. PID and other algorithms are used to keep liquid level and power balance. EPICS is adopt to integrate these platforms’along with vacuum devices, solid state amplifiers, LLRF and RF measurement system, etc. The details of the control system design, development and commissioning will be reported in this paper.
	Slides TUBR04 [22.084 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-TUBR04
About •	Received ※ 22 October 2021 Accepted ※ 11 February 2022 Issue date ※ 24 February 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUPV006	Control System of the SPIRAL2 Superconducting Linac Cryogenic System	controls, cryogenics, PLC, cavity	382
	A.H. Trudel, G. Duteil, A. Ghribi, Q. Tura GANIL, Caen, France P. Bonnay CEA/INAC, Grenoble Cedex 9, France
	The SPIRAL2 cryogenic system has been designed to cool down and maintain stable operation conditions of the 26 LINAC superconducting resonating cavities at a temperature of 4.5 K or lower. The control system of the cryogenic system of the LINAC is based on an architecture of 20 PLCs. Through an independent network, it drives the instrumentation, the cryogenic equipment, the 26 brushless motors of the frequency tuning system, interfaces the Epics Control System, and communicates process information to the Low Level Radio Frequency, vacuum, and magnet systems. Its functions are to ensure the safety of the cryogenic system, to efficiently control the cooldown of the 19 cryomodules, to enslave the frequency tuning system for the RF operation, and to monitor and analyze the data from the process. A model based Linear Quadratic regulation controls simultaneously both phase separators the liquid helium level and pressure. This control system also makes it possible to perform a number of virtual verification tests via a simulator and a dedicated PLC used to develop advanced model based control, such as a real time heat load estimator based on a Luenberger Filter
	Poster TUPV006 [2.393 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-TUPV006
About •	Received ※ 08 October 2021 Accepted ※ 23 February 2022 Issue date ※ 14 March 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUPV007	Motorized Regulation Systems for the SARAF Project	controls, PLC, cavity, feedback	387
	T.J. Joannem, F. Gohier, F. Gougnaud, P. Lotrus CEA-IRFU, Gif-sur-Yvette, France D. Darde CEA, DES-ISAS-DM2S, Université Paris-Saclay, Gif-sur-Yvette, France P. Guiho, A. Roger, N. Solenne CEA-DRF-IRFU, France
	CEA is in charge of the tuning regulation systems for the SARAF-Linac project. These tuning systems will be used with LLRF to regulate the 3 Rebuncher cavities and the HWR cavities of the 4 cryomodules. These systems were already tested on the Rebuncher and Equipped Cavity Test stands to test respectively the warm and cold tunings. This paper describes the hardware and software architectures. Both tuning systems are based on Siemens PLC and EPICS-PLC communication. Ambiant temperature technology is based on SIEMENS motor controller solution whereas the cold one combines Phytron and PhyMOTION solutions.
	Poster TUPV007 [0.892 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-TUPV007
About •	Received ※ 08 October 2021 Revised ※ 22 October 2021 Accepted ※ 05 February 2022 Issue date ※ 10 February 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEPV025	Initial Studies of Cavity Fault Prediction at Jefferson Laboratory	cavity, SRF, electron, data-acquisition	700
	L.S. Vidyaratne, A. Carpenter, R. Suleiman, C. Tennant, D.L. Turner JLab, Newport News, Virginia, USA K.M. Iftekharuddin, M. Rahman ODU, Norfolk, Virginia, USA
	Funding: This work supported by the U.S. Department of Energy, Office of Science, Office of Nuclear Physics under Contract No. DE-AC05-06OR23177. The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Laboratory is a CW recirculating linac that utilizes over 400 superconducting radio-frequency (SRF) cavities to accelerate electrons up to 12 GeV through 5-passes. Recent work has shown that, given RF signals from a cavity during a fault as input, machine learning approaches can accurately classify the fault type. In this paper we report on initial results of predicting a fault onset using only data prior to the failure event. A data set was constructed using time-series data immediately before a fault (’unstable’) and 1.5 seconds prior to a fault (’stable’) gathered from over 5,000 saved fault events. The data was used to train a binary classifier. The results gave key insights into the behavior of several fault types and provided motivation to investigate whether data prior to a failure event could also predict the type of fault. We discuss our method using a sliding window approach and report on initial results. Recent modifications to the low-level RF control system will provide access to streaming signals and we outline a path forward for leveraging deep learning on streaming data
	Poster WEPV025 [1.111 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-WEPV025
About •	Received ※ 08 October 2021 Revised ※ 19 October 2021 Accepted ※ 11 February 2022 Issue date ※ 05 March 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Other Keywords

Page

MOPV001

Status of the SARAF-Phase2 Control System

controls, EPICS, LLRF, network

93

F. Gougnaud, P. Bargueden, G. Desmarchelier, A. Gaget, P. Guiho, A. Lotode, Y. Mariette, V. Nadot, N. Solenne
CEA-DRF-IRFU, France
D. Darde, G. Ferrand, F. Gohier, T.J. Joannem, G. Monnereau, V. Silva
CEA-IRFU, Gif-sur-Yvette, France
H. Isakov, A. Perry, E. Reinfeld, I. Shmuely, Y. Solomon, N. Tamim
Soreq NRC, Yavne, Israel
T. Zchut
CEA LIST, Palaiseau, France

SNRC and CEA collaborate to the upgrade of the SARAF accelerator to 5 mA CW 40 Mev deuteron and proton beams and also closely to the control system. CEA is in charge of the Control System (including cabinets) design and implementation for the Injector (upgrade), MEBT and Super Conducting Linac made up of 4 cryomodules hosting HWR cavities and solenoid packages. This paper gives a detailed presentation of the control system architecture from hardware and EPICS software points of view. The hardware standardization relies on MTCA.4 that is used for LLRF, BPM, BLM and FC controls and on Siemens PLC 1500 series for vacuum, cryogenics and interlock. CEA IRFU EPICS Environment (IEE) platform is used for the whole accelerator. IEE is based on virtual machines and our MTCA.4 solutions and enables us to have homogenous EPICS modules. It also provides a development and production workflow. SNRC has integrated IEE into a new IT network based on advanced technology. The commissioning is planned to start late summer 2021.

Poster MOPV001 [1.787 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-MOPV001

About •

Received ※ 09 October 2021 Revised ※ 20 October 2021 Accepted ※ 03 November 2021 Issue date ※ 11 March 2022

Cite •

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

TUBR04

Control System of Cryomodule Test Facilities for SHINE*

controls, cryogenics, power-supply, monitoring

353

H.Y. Wang, G.H. Chen, J.F. Chen, J.G. Ding, M. Li, Y.J. Liu, Q.R. Mi, H.F. Miao, C.L. Yu
SSRF, Shanghai, People’s Republic of China

Funding: Work supported by Shanghai Municipal Science and Technology Major Project (Grant No. 2017SHZDZX02)
Shanghai HIgh repetition rate XFEL aNd Extreme light facility (SHINE) is under construction. The 8 GeV superconducting Linac consists of seventy-five 1.3 GHz and two 3.9 GHz cryomodules. A cryomodule assembling and test workshop is established. Multiple platforms have been built for cryomodule and superconducting cavity test, including two vertical test platforms, two horizontal test platform, one multiple test platform and one liquid helium visualization platform. The local control systems are all based on Yokogawa PLC, which monitor and control the process variables such as temperature, pressure, liquid level and power of the heater. PID and other algorithms are used to keep liquid level and power balance. EPICS is adopt to integrate these platforms’along with vacuum devices, solid state amplifiers, LLRF and RF measurement system, etc. The details of the control system design, development and commissioning will be reported in this paper.

Slides TUBR04 [22.084 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-TUBR04

About •

Received ※ 22 October 2021 Accepted ※ 11 February 2022 Issue date ※ 24 February 2022

Cite •

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

TUPV006

Control System of the SPIRAL2 Superconducting Linac Cryogenic System

controls, cryogenics, PLC, cavity

382

A.H. Trudel, G. Duteil, A. Ghribi, Q. Tura
GANIL, Caen, France
P. Bonnay
CEA/INAC, Grenoble Cedex 9, France

The SPIRAL2 cryogenic system has been designed to cool down and maintain stable operation conditions of the 26 LINAC superconducting resonating cavities at a temperature of 4.5 K or lower. The control system of the cryogenic system of the LINAC is based on an architecture of 20 PLCs. Through an independent network, it drives the instrumentation, the cryogenic equipment, the 26 brushless motors of the frequency tuning system, interfaces the Epics Control System, and communicates process information to the Low Level Radio Frequency, vacuum, and magnet systems. Its functions are to ensure the safety of the cryogenic system, to efficiently control the cooldown of the 19 cryomodules, to enslave the frequency tuning system for the RF operation, and to monitor and analyze the data from the process. A model based Linear Quadratic regulation controls simultaneously both phase separators the liquid helium level and pressure. This control system also makes it possible to perform a number of virtual verification tests via a simulator and a dedicated PLC used to develop advanced model based control, such as a real time heat load estimator based on a Luenberger Filter

Poster TUPV006 [2.393 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-TUPV006

About •

Received ※ 08 October 2021 Accepted ※ 23 February 2022 Issue date ※ 14 March 2022

Cite •

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

TUPV007

Motorized Regulation Systems for the SARAF Project

controls, PLC, cavity, feedback

387

T.J. Joannem, F. Gohier, F. Gougnaud, P. Lotrus
CEA-IRFU, Gif-sur-Yvette, France
D. Darde
CEA, DES-ISAS-DM2S, Université Paris-Saclay, Gif-sur-Yvette, France
P. Guiho, A. Roger, N. Solenne
CEA-DRF-IRFU, France

CEA is in charge of the tuning regulation systems for the SARAF-Linac project. These tuning systems will be used with LLRF to regulate the 3 Rebuncher cavities and the HWR cavities of the 4 cryomodules. These systems were already tested on the Rebuncher and Equipped Cavity Test stands to test respectively the warm and cold tunings. This paper describes the hardware and software architectures. Both tuning systems are based on Siemens PLC and EPICS-PLC communication. Ambiant temperature technology is based on SIEMENS motor controller solution whereas the cold one combines Phytron and PhyMOTION solutions.

Poster TUPV007 [0.892 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-TUPV007

About •

Received ※ 08 October 2021 Revised ※ 22 October 2021 Accepted ※ 05 February 2022 Issue date ※ 10 February 2022

Cite •

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

WEPV025

Initial Studies of Cavity Fault Prediction at Jefferson Laboratory

cavity, SRF, electron, data-acquisition

700

L.S. Vidyaratne, A. Carpenter, R. Suleiman, C. Tennant, D.L. Turner
JLab, Newport News, Virginia, USA
K.M. Iftekharuddin, M. Rahman
ODU, Norfolk, Virginia, USA

Funding: This work supported by the U.S. Department of Energy, Office of Science, Office of Nuclear Physics under Contract No. DE-AC05-06OR23177.
The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Laboratory is a CW recirculating linac that utilizes over 400 superconducting radio-frequency (SRF) cavities to accelerate electrons up to 12 GeV through 5-passes. Recent work has shown that, given RF signals from a cavity during a fault as input, machine learning approaches can accurately classify the fault type. In this paper we report on initial results of predicting a fault onset using only data prior to the failure event. A data set was constructed using time-series data immediately before a fault (’unstable’) and 1.5 seconds prior to a fault (’stable’) gathered from over 5,000 saved fault events. The data was used to train a binary classifier. The results gave key insights into the behavior of several fault types and provided motivation to investigate whether data prior to a failure event could also predict the type of fault. We discuss our method using a sliding window approach and report on initial results. Recent modifications to the low-level RF control system will provide access to streaming signals and we outline a path forward for leveraging deep learning on streaming data

Poster WEPV025 [1.111 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2021-WEPV025

About •

Received ※ 08 October 2021 Revised ※ 19 October 2021 Accepted ※ 11 February 2022 Issue date ※ 05 March 2022

Cite •

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