| Paper | Title | Page |
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| THSDSC01 | Sector Focused Cyclotron Power Supply Control System Upgrade | 1578 |
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| The old power supply control system of SFC (Sector Focused Cyclotron) has been in operation for more than a decade. Control system architecture is centralized, and equipment failure rate is getting higher and higher. The new control system uses the EPICS architecture, and the hardware uses Advantech’s APAX modules. The IOC runs on the APAX host and interacts with the module through API functions. The system has been running very stable for several months without failure. | ||
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Slides THSDSC01 [0.510 MB] | |
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Poster THSDSC01 [2.136 MB] | |
| DOI • | reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THSDSC01 | |
| About • | Received ※ 30 September 2023 — Revised ※ 11 October 2023 — Accepted ※ 06 December 2023 — Issued ※ 09 December 2023 | |
| Cite • | reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml) | |
THSDSC02 |
A High Resolution Multichannel Acquisition System for Magnetic Measurements of Fusion Experiments | |
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| Magnetic fusion experiments rely mainly on coil loops as the primary type of magnetic sensors, offering precision, reliability, and robustness. However, to analyze the magnetic field, the sensors signals need to be time-integrated. Usually, analog integrators were employed due to their wide dynamic range, but they present complexity challenges. The need for a separate channel for the derivative (dB/dt) signals is also required to measure fast events, plasma instabilities, and magnetic turbulences. In this work, we propose a novel system design based on high-resolution analog-to-digital converters (ADCs) that eliminates the need for analog integrators and the second acquisition channel, simplifying the overall system. The system uses 1 MS/s, 20-bit ADCs, electrically comparable to good analog integrators. To ensure accurate measurements, each acquisition channel is electrically isolated, effectively eliminating the ground loops generated by the experiment’s magnetic fields. The system architecture is implemented on 6U boards, where each board serves as an autonomous system housing 12 input channels and its own SOC-FPGA, with a total of 144 channels on a 6U sub-rack. Each board simultaneously provides three essential functionalities: a timing synchronization decoder, transient recording of full-speed ADC data, and continuous Ethernet UDP transmission of subsampled signals to the real-time control system. This comprehensive approach allows for efficient data acquisition, analysis, and integration into the experiment’s control framework. | ||
| Cite • | reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml) | |
| THSDSC03 | Integrate EPICS 7 with MATLAB Using PVAccess for Python (P4P) Module | 1580 |
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MATLAB is essential for accelerator scientists engaged in data analysis and processing across diverse fields, including particle physics experiments, synchrotron light sources, XFELs, and telescopes, due to its extensive range of built-in functions and tools. Scientists also depend on EPICS 7* to control and monitor complex systems. Since Python has gained popularity in the scientific community and many facilities have been migrating towards it, SLAC has developed matpva, a Python interface to integrate EPICS 7 with MATLAB. Matpva utilizes the Python P4P module** and EPICS 7 to offer a robust and reliable interface for MATLAB users that employ EPICS 7. The EPICS 7 PVAccess API allows higher-level scientific applications to get/set/monitor simple and complex structures from an EPICS 7-based control system. Moreover, matpva simplifies the process by handling the data type conversion from Python to MATLAB, making it easier for researchers to focus on their analyses and innovative ideas instead of technical data conversion. By leveraging matpva, researchers can work more efficiently and make discoveries in diverse fields, including particle physics and astronomy.
* See https://epics-controls.org/resources-and-support/base/epics-7/ to learn more about EPICS 7 ** Visit https://mdavidsaver.github.io/p4p/ to learn more about the P4P |
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Poster THSDSC03 [0.865 MB] | |
| DOI • | reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THSDSC03 | |
| About • | Received ※ 06 October 2023 — Revised ※ 10 October 2023 — Accepted ※ 06 December 2023 — Issued ※ 15 December 2023 | |
| Cite • | reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml) | |
| THSDSC04 | CamServer: Stream Processing at SwissFEL and SLS 2.0 | 1585 |
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| CamServer is a Python package for data stream processing developed at Paul Scherrer Institute (PSI). It is a key component of SwissFEL’s data acquisition, where it is deployed on a cluster of servers and used for displaying and processing images from all cameras. It scales linearly with the number of servers and is capable of handling multiple high-resolution cameras at 100Hz, as well as a variety of data types and sources. The processing unit, called a pipeline, runs in a private process that can be either permanent or spawned on demand. Pipelines consume and produce ZMQ streams, but input data can be arbitrary using an adapter layer (e.g. EPICS). A proxy server handles requests and creates pipelines on the cluster’s worker nodes according to rules. Some processing scripts are available out of the box (e.g. calculation of standard beam metrics) but users can upload custom ones. The system is managed via its REST API, using a client library or a GUI application. CamServer’s output data streams are consumed by a variety of client types such as data storage, image visualization, monitoring and DAQ applications. This work describes the use of CamServer, the status of the SwissFEL’s cluster and the development roadmap with plans for SLS 2.0. | ||
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Poster THSDSC04 [1.276 MB] | |
| DOI • | reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THSDSC04 | |
| About • | Received ※ 03 October 2023 — Revised ※ 10 October 2023 — Accepted ※ 06 December 2023 — Issued ※ 19 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 | 1590 |
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| 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. | ||
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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) | |
| THSDSC06 | Developing a Digital Twin for BESSY II Synchrotron Light Source Based on EPICS and Microservice Design | 1594 |
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| Digital twins, i.e. theory and design tools connected to the real devices and machine by mapping of physics components to the technical correspondents, are powerful tools providing accelerators with commissioning predictions and feedback capabilities. This paper describes a new tool allowing for greater flexibility in configuring the modelling part combined with ease of adding new features. To enable the various components developed in EPICS, Python, C, and C++ to work together seamlessly, we adopt a microservice architecture, with REST API services providing the interfaces between the components. End user scripts are implemented as REST API services, allowing for better data analysis and visualization. Finally, the paper describes the integration of dash and ploty for enhanced data comparison and visualization. Overall, this workflow provides a powerful and flexible solution for managing and optimizing BESSY II digital twins, with the potential for further customization and extension to upcoming machines. | ||
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Poster THSDSC06 [0.797 MB] | |
| DOI • | reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THSDSC06 | |
| About • | Received ※ 05 October 2023 — Revised ※ 27 October 2023 — Accepted ※ 05 November 2023 — Issued ※ 05 December 2023 | |
| Cite • | reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml) | |