Paper | Title | Other Keywords | Page |
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MO3AO07 | Control Design Optimisations of Robots for the Maintenance and Inspection of Particle Accelerators | controls, operation, interface, software | 153 |
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Automated maintenance and inspection systems have become increasingly important over the last decade for the availability of the accelerators at CERN. This is mainly due to improvements in robotic perception, control and cognition and especially because of the rapid advancement in artificial intelligence. The robotic service at CERN performed the first interventions in 2014 with robotic solutions from external companies. However, it soon became clear that a customized platform needed to be developed in order to satisfy the needs and in order to efficiently navigate through the cluttered, semi-structured environment. This led to the formation of a robotic fleet of about 20 different robotic systems that are currently active at CERN. In order to increase the efficiency and robustness of robotic platforms for future accelerators it is necessary to consider robotic interventions at the early design phase of such machines. Task specific solutions tailored to the specific needs can then be designed, which in general show higher efficiency than multipurpose industrial robotic systems. This paper presents current advances in the design and development of task specific robotic system for maintenance and inspection in particle accelerators, taking the 100 km long Future Circular Collider main tunnel as a use case. The requirements on such a robotic system, including the applied control strategies, are shown, as well as the optimization of the topology and geometry of the robotic system itself. | |||
Slides MO3AO07 [3.560 MB] | |||
DOI • | reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-MO3AO07 | ||
About • | Received ※ 29 September 2023 — Revised ※ 10 October 2023 — Accepted ※ 14 November 2023 — Issued ※ 26 November 2023 | ||
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TU2AO02 | Textual Analysis of ICALEPCS and IPAC Conference Proceedings: Revealing Research Trends, Topics, and Collaborations for Future Insights and Advanced Search | cryogenics, controls, laser, LLRF | 309 |
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Funding: This work was supported by HamburgX grant LFF-HHX-03 to the Center for Data and Computing in Natural Sciences (CDCS) from the Hamburg Ministry of Science, Research, Equalities and Districts. In this paper, we show a textual analysis of past ICALEPCS and IPAC conference proceedings to gain insights into the research trends and topics discussed in the field. We use natural language processing techniques to extract meaningful information from the abstracts and papers of past conference proceedings. We extract topics to visualize and identify trends, analyze their evolution to identify emerging research directions and highlight interesting publications based solely on their content with an analysis of their network. Additionally, we will provide an advanced search tool to better search in the existing papers to prevent duplication and easier reference findings. Our analysis provides a comprehensive overview of the research landscape in the field and helps researchers and practitioners to better understand the state-of-the-art and identify areas for future research. |
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Slides TU2AO02 [12.762 MB] | |||
DOI • | reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TU2AO02 | ||
About • | Received ※ 30 September 2023 — Revised ※ 11 October 2023 — Accepted ※ 18 November 2023 — Issued ※ 29 November 2023 | ||
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TUMBCMO12 | Multi-Dimensional Spectrogram Application for Live Visualization and Manipulation of Large Waveforms | controls, EPICS, proton, real-time | 368 |
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The European Spallation Source (ESS) is a research facility under construction aiming to be the world’s most powerful pulsed neutron source. It is powered by a complex particle accelerator designed to provide a 2.86 ms long proton pulse at 2 GeV with a repetition rate of 14 Hz. Protons are accelerated via cavity fields through various accelerating structures that are powered by Radio-Frequency (RF) power. As the cavity fields may break down due to various reasons, usually post-mortem data of such events contain the information needed regarding the cause. In other events, the underlying cause may have been visible on previous beam pulses before the interlock triggering event. The Multi-Dimensional Spectrogram Application is designed to be able to collect, manipulate and visualize large waveforms at high repetition rates, with the ESS goal being 14 Hz, for example cavity fields, showing otherwise unnoticed temporary breakdowns that may explain the sometimes-unknown reason for increased power (compensating for those invisible temporary breakdowns). The first physical event that was recorded with the tool was quenching of a superconducting RF cavity in real time in 3D. This paper describes the application developed using Python and the pure-python graphics and GUI library PyQtGraph and PyQt5 with Python-OpenGL bindings. | |||
Slides TUMBCMO12 [2.932 MB] | |||
Poster TUMBCMO12 [11.475 MB] | |||
DOI • | reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUMBCMO12 | ||
About • | Received ※ 04 October 2023 — Accepted ※ 23 November 2023 — Issued ※ 23 November 2023 | ||
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TUMBCMO14 | Initial Test of a Machine Learning Based SRF Cavity Active Resonance Control | controls, SRF, resonance, simulation | 379 |
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We’ll introduce a high precision active motion controller based on machine learning (ML) technology and electric piezo actuator. The controller will be used for SRF cavity active resonance control, where a data-driven model for system motion dynamics will be developed first, and a model predictive controller (MPC) will be built accordingly. Simulation results as well as initial test results with real SRF cavities will be presented in the paper. | |||
DOI • | reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUMBCMO14 | ||
About • | Received ※ 03 October 2023 — Revised ※ 14 November 2023 — Accepted ※ 27 November 2023 — Issued ※ 09 December 2023 | ||
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TUMBCMO30 | EPICS Based Tool for LLRF Operation Support and Testing | controls, EPICS, LLRF, operation | 432 |
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Interruptions in the functioning of linear superconductive accelerators LLRF (Low-Level Radio Frequency) systems can result in significant downtime. This can lead to lost productivity and revenue. Accelerators are foreseen to operate under various conditions and in different operating modes. As such, it is crucial to have flexibility in their operation to adapt to demands. Automation is a potential solution to address these challenges by reducing the need for human intervention and improving the control’s quality over the accelerator. The paper describes EPICS-based tools for LLRF control system testing, optimization, and operations support. The proposed software implements procedures and applications that are usually extensions to the core LLRF systems functionalities and are performed by operators. This facilitates the maintenance of the accelerator and increases its flexibility in adaptation to various work conditions and can increase its availability level. The paper focuses on the architecture of the solution. It also depicts its components related to superconducting cavities parameters identification and elements responsible for their tuning. Since the proposed solution is destined for the European Spallation Source control system, the application has a form of multiple IOCs (Input/Output Controllers) wrapped into E3 (ESS EPICS Environment) modules. Nevertheless, it can be adjusted to other control systems - its logic is universal and applicable (after adaptations) to other LLRF control systems with superconducting cavities. | |||
Slides TUMBCMO30 [0.466 MB] | |||
DOI • | reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUMBCMO30 | ||
About • | Received ※ 06 October 2023 — Revised ※ 12 October 2023 — Accepted ※ 28 November 2023 — Issued ※ 30 November 2023 | ||
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TUPDP080 | Automated Procedure for Conditioning of Normal Conducting Accelerator Cavities | controls, DTL, linac, vacuum | 699 |
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Radio frequency (RF) conditioning is an essential stage during the preparation of particle accelerator cavities for operation. During this process the cavity field is gradually increased to the nominal parameters enabling the outgassing of the cavity and the elimination of surface defects through electrical arcing. However, this process can be time-consuming and labor-intensive, requiring skilled operators to carefully adjust the RF parameters. This proceeding presents the software tools for the development of an automatized EPICS control application with the aim to accelerate and introduce flexibility to the conditioning process. The results from the conditioning process of the ESS Radio-Frequency Quadrupole (RFQ) and the parallel conditioning of Drift-Tube Linac (DTL) tanks will be presented demonstrating the potential to save considerable time and resources in future RF conditioning campaigns. | |||
Poster TUPDP080 [17.411 MB] | |||
DOI • | reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUPDP080 | ||
About • | Received ※ 04 October 2023 — Accepted ※ 12 December 2023 — Issued ※ 13 December 2023 | ||
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TUPDP085 | EPICS at FREIA Laboratory | controls, EPICS, PLC, software | 718 |
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FREIA laboratory is a Facility for REsearch Instrumentation and Accelerator development at Uppsala University, Sweden. It was officially open in 2013 to test and develop superconducting accelerating cavities and their high power RF sources. The laboratory focuses on superconducting technology and accelerator development and conducts research on beam physics and light generation with charged particles, accelerator technology and instrumentation. From the very beginning EPICS* has been chosen as a control system for all the infrastructure and equipment in the lab. Use of EPICS allowed us to build a robust, expandable and maintainable control system with a very limited man power. The paper will present the choices we made and the problems we have solved to achieve this goal. We will show the current status of the control system and the strategy for the future.
* https://epics-controls.org/ |
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Poster TUPDP085 [2.305 MB] | |||
DOI • | reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUPDP085 | ||
About • | Received ※ 27 September 2023 — Revised ※ 09 October 2023 — Accepted ※ 14 December 2023 — Issued ※ 18 December 2023 | ||
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TUPDP115 | Machine Learning for Compact Industrial Accelerators | controls, simulation, industrial-accelerators, network | 846 |
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Funding: This material is based upon work supported by the DOE Accelerator R&D and Production under Award Number DE-SC0023641. The industrial and medical accelerator industry is an ever-growing field with advancements in accelerator technology enabling its adoption for new applications. As the complexity of industrial accelerators grows so does the need for more sophisticated control systems to regulate their operation. Moreover, the environment for industrial and medical accelerators is often harsh and noisy as opposed to the more controlled environment of a laboratory-based machine. This environment makes control more challenging. Additionally, instrumentation for industrial accelerators is limited making it difficult at times to identify and diagnose problems when they occur. RadiaSoft has partnered with SLAC to develop new machine learning methods for control and anomaly detection for industrial accelerators. Our approach is to develop our methods using simulation models followed by testing on experimental systems. Here we present initial results using simulations of a room temperature s-band system. |
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DOI • | reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUPDP115 | ||
About • | Received ※ 06 October 2023 — Accepted ※ 05 December 2023 — Issued ※ 18 December 2023 | ||
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TUPDP131 | Longitudinal Feedback for the LCLS-II Superconducting Linear Accelerator at SLAC | feedback, linac, controls, electron | 895 |
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Funding: U.S. Department of Energy under Grant No. DE-AC02-76SF00515 SLAC recently commissioned a new continuous-wave, MHz repetition-rate Superconducting (SC) Linear Accelerator (Linac). This accelerator can produce a 4 GeV electron beam that drives two dedicated Hard and Soft X-ray Undulator lines as part of the Linac Coherent Light Source (LCLS) Free Electron Laser. A new Python-based longitudinal feedback is used to control the electron beam energy and bunch length along the accelerator. This feedback was written to be simple, easily maintainable and easily portable for use on other accelerators or systems as a general-purpose feedback with minimal dependencies. Design and operational results of the feedback will be discussed, along with the Graphical User Interfaces built using Python Display Manager (PyDM). |
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Poster TUPDP131 [2.221 MB] | |||
DOI • | reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUPDP131 | ||
About • | Received ※ 29 September 2023 — Revised ※ 12 October 2023 — Accepted ※ 13 October 2023 — Issued ※ 14 October 2023 | ||
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WE3AO05 | Helium Mass Flow System Integrated into EPICS for Online SRF Cavity Q Measurements | cryomodule, controls, operation, interface | 1071 |
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The SBIR funded Helium Mass Flow Monitor System, developed by Jefferson Lab and Hyperboloid LLC, is designed to measure the health of cavities in a Cryomodule in real-time. It addresses the problem of cavities with low Q₀, which generate excess heat and evaporation from the 2 K super-fluid helium bath used to cool the cavities. The system utilizes a unique meter that is based on a superconducting component. This device enables high-resolution measurements of the power dissipated in the cryomodule while the accelerator is operating. It can also measure individual Cavity Q₀s when the beam is turned off. The Linux-based control system is an integral part of this device, providing the necessary control and data processing capabilities. The initial implementation of the Helium Mass Flow Monitor System at Jefferson Lab was done using LabView, a couple of current sources & a nano-voltmeter. Once the device was proven to work at 2K the controls transitioned to a hand wired PCB & Raspberry Pi interfaced to the open-source Experimental Physics and Industrial Control System (EPICS) control system. The EE support group preferred to support a LabJack T7 over the rPi. 12 chassis were built and the system is being deployed as the cryogenic U-Tubes become available. | |||
Slides WE3AO05 [6.073 MB] | |||
DOI • | reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-WE3AO05 | ||
About • | Received ※ 09 October 2023 — Revised ※ 12 October 2023 — Accepted ※ 14 December 2023 — Issued ※ 18 December 2023 | ||
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THPDP017 | A Data Acquisition Middle Layer Server with Python Support for Linac Operation and Experiments Monitoring and Control | FEL, controls, operation, experiment | 1330 |
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This paper presents online anomaly detection on low-level radio frequency (LLRF) cavities running on FLASH/XFEL DAQ system*. The code is run by a DAQ Middle Layer (ML) server, which has on-line access to all collected data. The ML server executes a Python script that runs a pre-trained machine learning model on every shot in the FLASH/XFEL machine. We discuss the challenges associated with real-time anomaly detection due to high data rates generated by RF cavities, and introduce a DAQ system pipeline and algorithms used for online detection on arbitrary channels in our control system. The system’s performance is evaluated using real data from operational RF cavities. We also focus on the DAQ monitor server’s features and its implementation.
*A. Aghababyan et al., ’Multi-Processor Based Fast Data Acquisition for a Free Electron Laser and Experiments’, in IEEE Transactions on Nuclear Science, vol. 55, No. 1, pp. 256-260, February 2008 |
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DOI • | reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THPDP017 | ||
About • | Received ※ 02 October 2023 — Revised ※ 25 October 2023 — Accepted ※ 13 December 2023 — Issued ※ 20 December 2023 | ||
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THPDP028 | Particle Swarm Optimization Techniques for Automatic Beam Transport at the Lnl Superconducting Linac Accelerators | EPICS, controls, beam-transport, linac | 1370 |
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The superconductive quarter wave cavities hadron Lin-ac ALPI is the final acceleration stage at the Legnaro National Laboratories and it is going to be used as re-acceleration line of the radioactive ion beams for the SPES (Selective Production of Exotic Species) project. The Linac was designed in ’90s with the available techniques and it was one of the peak technologies of this kind in Europe at those times, controls included. In the last decade, controls related to all the functional systems composing the accelerator have been ungraded to an EPICS-based solution. This upgrade has given us the opportunity to design and test new possible solutions for automatic beam transport. The work described in this paper is based on the experience and results (in terms of time, costs, and manpower) obtained using Particle Swarm Optimization (PSO) techniques for beam transport optimization applied to the ALPI accelerator. Due to the flexibility and robustness of this method, this tool will be extended to other parts of the facility. | |||
DOI • | reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THPDP028 | ||
About • | Received ※ 06 September 2023 — Revised ※ 10 October 2023 — Accepted ※ 10 December 2023 — Issued ※ 16 December 2023 | ||
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THPDP051 | LLRF and Timing System Integration at ESS | LLRF, timing, controls, MMI | 1426 |
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The Low Level Radio Frequency (LLRF) system is an important part of a Spallation Source facility as ESS. LLRF is commonly used with many different setups depending on the aim: preparation, calibration, conditioning, commission and others. These different setups are strongly connected to another important system on accelerators: the Timing System. This proceeding presents how at ESS we implemented the integration between LLRF and Timing systems on the control system scope. The integration of these two systems provides different and important features as: allow different ways to trigger the RF system (synced or not to other systems), define how the RF output will be defined (based on the features of the expected beam), re-configure LLRF depending on the timing setup and more. This integration was developed on both ends, LLRF and timing, and is mostly concentrated on the control system layer based on EPICS. Dealing with the different scenarios, synchronicity and considering all the software, hardware and firmware involved are some of the challenges of this integration. The result of this work was used during the ESS accelerator commissioning in 2022 and will be used on next ESS accelerator commissioning in 2023. | |||
Poster THPDP051 [0.993 MB] | |||
DOI • | reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THPDP051 | ||
About • | Received ※ 05 October 2023 — Accepted ※ 08 December 2023 — Issued ※ 12 December 2023 | ||
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FR2AO04 | A Physics-Based Simulator to Facilitate Reinforcement Learning in the RHIC Accelerator Complex | controls, booster, simulation, diagnostics | 1630 |
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Funding: Work supported by Brookhaven Science Associates, LLC under Contract No. DE-SC0012704 with the U.S. Department of Energy. The successful use of machine learning (ML) in particle accelerators has greatly expanded in recent years; however, the realities of operations often mean very limited machine availability for ML development, impeding its progress in many cases. This paper presents a framework for exploiting physics-based simulations, coupled with real machine data structure, to facilitate the investigation and implementation of reinforcement learning (RL) algorithms, using the longitudinal bunch-merge process in the Booster and Alternating Gradient Synchrotron (AGS) at Brookhaven National Laboratory (BNL) as examples. Here, an initial fake wall current monitor (WCM) signal is fed through a noisy physics-based model simulating the behavior of bunches in the accelerator under given RF parameters and external perturbations between WCM samples; the resulting output becomes the input for the RL algorithm and subsequent pass through the simulated ring, whose RF parameters have been modified by the RL algorithm. This process continues until an optimal policy for the RF bunch merge gymnastics has been learned for injecting bunches with the required intensity and emittance into the Relativistic Heavy Ion Collider (RHIC), according to the physics model. Robustness of the RL algorithm can be evaluated by introducing other drifts and noisy scenarios before the algorithm is deployed and final optimization occurs in the field. |
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Slides FR2AO04 [2.694 MB] | |||
DOI • | reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-FR2AO04 | ||
About • | Received ※ 04 October 2023 — Accepted ※ 05 December 2023 — Issued ※ 16 December 2023 | ||
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