IBIC2023 - List of Keywords (network)

Paper	Title	Other Keywords	Page
MO3C05	Canadian Light Source Beam Position Visualization Tool	EPICS, controls, operation, storage-ring	24
	M. Bree, T. Batten, C.W. Stevens, J.M. Vogt CLS, Saskatoon, Saskatchewan, Canada
	The CLS Orbit Correction (OC) system acquires, collates, and publishes storage ring beam centroid position information from 48 beam position monitors (BPMs) at a rate of 1000 samples per second. We present a "Storage Ring Beam Position Visualization Tool" that computes and displays dynamic Fast Fourier Transforms (FFTs) and Cumulative Power Spectral Densities (CPSDs) for all BPMs in real-time using full resolution data. The computed FFTs and CPSDs can be plotted in various combinations and in waterfall plots that allow visualization of changes over long periods of time. In addition, correlations between all BPM channel combinations are computed and ranked. Data from any two BPM channels can be selected for plotting in two dimensions wherein correlations are visually apparent. Computed CPSDs are further binned and published in scalar EPICS PVs which are archived for further analysis. Preliminary results from the Beam Position Visualization Tool have proven useful in characterizing beam position noise at the CLS.
	Slides MO3C05 [197.014 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-IBIC2023-MO3C05
About •	Received ※ 17 July 2023 — Revised ※ 16 August 2023 — Accepted ※ 13 September 2023 — Issue date ※ 26 September 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

MOP023	The Conceptual Design Study for New BPM Signal Processing System of J-PARC (MR)	impedance, operation, controls, FPGA	78
	K. Satou, T. Toyama, S. Yamada KEK, Tokai, Ibaraki, Japan
	The BPM signal processing system, which is19 years old system, have been suffering from gain fluctuation due to contact resistance of the mechanical gain selector, communication disruption caused by an unstable contact of a card edge connector. In addition, it has a difficulty of repairments because some on-board parts have already reached end of product-life cycle, and some units have been in unusable situation. Presently, we are on the beam power upgrade campaign to 1.3 MW by increasing beam bunch current and shortening the MR operation cycle, and precise beam tunings would require massive waveform data processing and transfer to a storage than the present system. For this, we have been developing the system based on the 10 GbE optical link. The ADC board which is under development would perform direct sampling using the third harmonic of RF. The digital IQ demodulation technique is used to extract the baseband oscillation from the raw data. The obtained raw waveform as well as closed orbit data would be stored in the data storage system. In the presentation, we will report on the progress of development aimed at operation in 2025 and the conceptual design of the new system.
DOI •	reference for this paper ※ doi:10.18429/JACoW-IBIC2023-MOP023
About •	Received ※ 06 September 2023 — Revised ※ 07 September 2023 — Accepted ※ 13 September 2023 — Issue date ※ 19 September 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

MOP036	A New Approach for Canadian Light Source Future Orbit Correction System Driven by Neural Network	ECR, storage-ring, experiment, real-time	102
	S. Saadat, M.J. Boland CLS, Saskatoon, Saskatchewan, Canada M.J. Boland University of Saskatchewan, Saskatoon, Canada
	The Orbit Correction System (OCS) of the CLS comprises 48 sets of BPMs. Each BPM has the ability to measure the position of the beam in both the X-Y directions and can record data at a rate of 900 times per second. The Inverse Response Matrix is utilized to determine the optimal strength of the 48 sets of orbit correctors in both the X-Y directions, in order to ensure that the beam follows its desired path. The Singular Value Decomposition function is replaced by a neural network algorithm to serve as the brain of the orbit correction system in this study. The training model’s design includes three hidden layers, and within each layer, there are 96 nodes. The neural network’s outputs for regular operations in CLS exhibit a Mean Square Error of 10^-7. Various difficult scenarios were created to test the OCS at 8.0 mA, using offsets in different sections of the storage ring. However, the new model was able to produce the necessary Orbit Correctors signals without any trouble.
	Poster MOP036 [1.438 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-IBIC2023-MOP036
About •	Received ※ 14 July 2023 — Revised ※ 09 September 2023 — Accepted ※ 28 September 2023 — Issue date ※ 30 September 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TU3C02	FPGA Architectures for Distributed ML Systems for Real-Time Beam Loss De-Blending	real-time, distributed, operation, FPGA	160
	M.A. Ibrahim, J.M.S. Arnold, M.R. Austin, J.R. Berlioz, P.M. Hanlet, K.J. Hazelwood, J. Mitrevski, V.P. Nagaslaev, A. Narayanan, D.J. Nicklaus, G. Pradhan, A.L. Saewert, B.A. Schupbach, K. Seiya, R.M. Thurman-Keup, N.V. Tran Fermilab, Batavia, Illinois, USA J.YC. Hu, J. Jiang, H. Liu, S. Memik, R. Shi, A.M. Shuping, M. Thieme, C. Xu Northwestern University, EVANSTON, USA
	Funding: Operated by Fermi Research Alliance, LLC under Contract No.DE-AC02-07CH11359 with the United States Department of Energy. Additional funding provided by Grant Award No. LAB 20-2261 [1] The Real-time Edge AI for Distributed Systems (READS) project’s goal is to create a Machine Learning (ML) system for real-time beam loss de-blending within the accelerator enclosure, which houses two accelerators: the Main Injector (MI) and the Recycler (RR). In periods of joint operation, when both machines contain high intensity beam, radiative beam losses from MI and RR overlap on the enclosure¿s beam loss monitoring (BLM) system, making it difficult to attribute those losses to a single machine. Incorrect diagnoses result in unnecessary downtime that incurs both financial and experimental cost. The ML system will automatically disentangle each machine¿s contributions to those measured losses, while not disrupting the existing operations-critical functions of the BLM system. Within this paper, the ML models, used for learning both local and global machine signatures and producing high quality inferences based on raw BLM loss measurements, will only be discussed at a high-level. This paper will focus on the evolution of the architecture, which provided the high-frequency, low-latency collection of synchronized data streams to make real-time inferences. Performed at Northwestern with support from the Departments of Computer Science and Electrical and Computer Engineering
	Slides TU3C02 [17.830 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-IBIC2023-TU3C02
About •	Received ※ 07 September 2023 — Revised ※ 10 September 2023 — Accepted ※ 12 September 2023 — Issue date ※ 25 September 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEP046	Progress on Distributed Image Analysis from Digital Cameras at ELSA using the RabbitMQ Message Broker	interface, framework, controls, distributed	449
	M.T. Switka, K. Desch, T.J. Gereons, S. Kronenberg, D. Proft, A. Spreitzer ELSA, Bonn, Germany
	In the course of modernization of camera based imaging and image analysis for accelerator hardware and beam control at the ELSA facility, a distributed image processing approach was implemented, called FGrabbit. We utilize the RabbitMQ message broker to share the high data throughput from image acquisition, processing, analysis, display and storage between different work stations to achieve an optimum efficacy of the involved hardware. Re-calibration of already deployed beam profile monitors using machine vision algorithms allow us to perform qualitative beam photometry measurements to obtain beam sizes and dynamics with good precision. We describe the robustness of the calibration, image acquisition and processing and present the architecture and applications, such as the programming- and web-interface for machine operators and developers.
DOI •	reference for this paper ※ doi:10.18429/JACoW-IBIC2023-WEP046
About •	Received ※ 07 September 2023 — Revised ※ 08 September 2023 — Accepted ※ 15 September 2023 — Issue date ※ 28 September 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Other Keywords

Page

MO3C05

Canadian Light Source Beam Position Visualization Tool

EPICS, controls, operation, storage-ring

24

M. Bree, T. Batten, C.W. Stevens, J.M. Vogt
CLS, Saskatoon, Saskatchewan, Canada

The CLS Orbit Correction (OC) system acquires, collates, and publishes storage ring beam centroid position information from 48 beam position monitors (BPMs) at a rate of 1000 samples per second. We present a "Storage Ring Beam Position Visualization Tool" that computes and displays dynamic Fast Fourier Transforms (FFTs) and Cumulative Power Spectral Densities (CPSDs) for all BPMs in real-time using full resolution data. The computed FFTs and CPSDs can be plotted in various combinations and in waterfall plots that allow visualization of changes over long periods of time. In addition, correlations between all BPM channel combinations are computed and ranked. Data from any two BPM channels can be selected for plotting in two dimensions wherein correlations are visually apparent. Computed CPSDs are further binned and published in scalar EPICS PVs which are archived for further analysis. Preliminary results from the Beam Position Visualization Tool have proven useful in characterizing beam position noise at the CLS.

Slides MO3C05 [197.014 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-IBIC2023-MO3C05

About •

Received ※ 17 July 2023 — Revised ※ 16 August 2023 — Accepted ※ 13 September 2023 — Issue date ※ 26 September 2023

Cite •

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

MOP023

The Conceptual Design Study for New BPM Signal Processing System of J-PARC (MR)

impedance, operation, controls, FPGA

78

K. Satou, T. Toyama, S. Yamada
KEK, Tokai, Ibaraki, Japan

The BPM signal processing system, which is19 years old system, have been suffering from gain fluctuation due to contact resistance of the mechanical gain selector, communication disruption caused by an unstable contact of a card edge connector. In addition, it has a difficulty of repairments because some on-board parts have already reached end of product-life cycle, and some units have been in unusable situation. Presently, we are on the beam power upgrade campaign to 1.3 MW by increasing beam bunch current and shortening the MR operation cycle, and precise beam tunings would require massive waveform data processing and transfer to a storage than the present system. For this, we have been developing the system based on the 10 GbE optical link. The ADC board which is under development would perform direct sampling using the third harmonic of RF. The digital IQ demodulation technique is used to extract the baseband oscillation from the raw data. The obtained raw waveform as well as closed orbit data would be stored in the data storage system. In the presentation, we will report on the progress of development aimed at operation in 2025 and the conceptual design of the new system.

DOI •

reference for this paper ※ doi:10.18429/JACoW-IBIC2023-MOP023

About •

Received ※ 06 September 2023 — Revised ※ 07 September 2023 — Accepted ※ 13 September 2023 — Issue date ※ 19 September 2023

Cite •

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

MOP036

A New Approach for Canadian Light Source Future Orbit Correction System Driven by Neural Network

ECR, storage-ring, experiment, real-time

102

S. Saadat, M.J. Boland
CLS, Saskatoon, Saskatchewan, Canada
M.J. Boland
University of Saskatchewan, Saskatoon, Canada

The Orbit Correction System (OCS) of the CLS comprises 48 sets of BPMs. Each BPM has the ability to measure the position of the beam in both the X-Y directions and can record data at a rate of 900 times per second. The Inverse Response Matrix is utilized to determine the optimal strength of the 48 sets of orbit correctors in both the X-Y directions, in order to ensure that the beam follows its desired path. The Singular Value Decomposition function is replaced by a neural network algorithm to serve as the brain of the orbit correction system in this study. The training model’s design includes three hidden layers, and within each layer, there are 96 nodes. The neural network’s outputs for regular operations in CLS exhibit a Mean Square Error of 10^-7. Various difficult scenarios were created to test the OCS at 8.0 mA, using offsets in different sections of the storage ring. However, the new model was able to produce the necessary Orbit Correctors signals without any trouble.

Poster MOP036 [1.438 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-IBIC2023-MOP036

About •

Received ※ 14 July 2023 — Revised ※ 09 September 2023 — Accepted ※ 28 September 2023 — Issue date ※ 30 September 2023

Cite •

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

TU3C02

FPGA Architectures for Distributed ML Systems for Real-Time Beam Loss De-Blending

real-time, distributed, operation, FPGA

160

M.A. Ibrahim, J.M.S. Arnold, M.R. Austin, J.R. Berlioz, P.M. Hanlet, K.J. Hazelwood, J. Mitrevski, V.P. Nagaslaev, A. Narayanan, D.J. Nicklaus, G. Pradhan, A.L. Saewert, B.A. Schupbach, K. Seiya, R.M. Thurman-Keup, N.V. Tran
Fermilab, Batavia, Illinois, USA
J.YC. Hu, J. Jiang, H. Liu, S. Memik, R. Shi, A.M. Shuping, M. Thieme, C. Xu
Northwestern University, EVANSTON, USA

Funding: Operated by Fermi Research Alliance, LLC under Contract No.DE-AC02-07CH11359 with the United States Department of Energy. Additional funding provided by Grant Award No. LAB 20-2261 [1]
The Real-time Edge AI for Distributed Systems (READS) project’s goal is to create a Machine Learning (ML) system for real-time beam loss de-blending within the accelerator enclosure, which houses two accelerators: the Main Injector (MI) and the Recycler (RR). In periods of joint operation, when both machines contain high intensity beam, radiative beam losses from MI and RR overlap on the enclosure¿s beam loss monitoring (BLM) system, making it difficult to attribute those losses to a single machine. Incorrect diagnoses result in unnecessary downtime that incurs both financial and experimental cost. The ML system will automatically disentangle each machine¿s contributions to those measured losses, while not disrupting the existing operations-critical functions of the BLM system. Within this paper, the ML models, used for learning both local and global machine signatures and producing high quality inferences based on raw BLM loss measurements, will only be discussed at a high-level. This paper will focus on the evolution of the architecture, which provided the high-frequency, low-latency collection of synchronized data streams to make real-time inferences.
Performed at Northwestern with support from the Departments of Computer Science and Electrical and Computer Engineering

Slides TU3C02 [17.830 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-IBIC2023-TU3C02

About •

Received ※ 07 September 2023 — Revised ※ 10 September 2023 — Accepted ※ 12 September 2023 — Issue date ※ 25 September 2023

Cite •

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

WEP046

Progress on Distributed Image Analysis from Digital Cameras at ELSA using the RabbitMQ Message Broker

interface, framework, controls, distributed

449

M.T. Switka, K. Desch, T.J. Gereons, S. Kronenberg, D. Proft, A. Spreitzer
ELSA, Bonn, Germany

In the course of modernization of camera based imaging and image analysis for accelerator hardware and beam control at the ELSA facility, a distributed image processing approach was implemented, called FGrabbit. We utilize the RabbitMQ message broker to share the high data throughput from image acquisition, processing, analysis, display and storage between different work stations to achieve an optimum efficacy of the involved hardware. Re-calibration of already deployed beam profile monitors using machine vision algorithms allow us to perform qualitative beam photometry measurements to obtain beam sizes and dynamics with good precision. We describe the robustness of the calibration, image acquisition and processing and present the architecture and applications, such as the programming- and web-interface for machine operators and developers.

DOI •

reference for this paper ※ doi:10.18429/JACoW-IBIC2023-WEP046

About •

Received ※ 07 September 2023 — Revised ※ 08 September 2023 — Accepted ※ 15 September 2023 — Issue date ※ 28 September 2023

Cite •

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