Data Acquisition and Data Storage, Data Analysis
Paper Title Page
THPP4
The Trip Event Logger – a Fault Diagnosis Tool  
THP08   use link to see paper's listing under its alternate paper code  
 
  • J.H.K. Timm, J. Branlard, A. Eichler
    DESY, Hamburg, Germany
 
  The low-level RF (LLRF) system at the European XFEL, DESY, is of major importance for high-performant and reliable operation. Faults here can jeopardize the overall operation. Therefore, the trip event logger is currently developed, - a fault diagnosis tool to detect errors online, inform the operators and trigger automatic supervisory actions. Further goals are to provide information for a fault tree and event tree analysis as well as a database of labeled faultydata sets for offline analysis. The tool is based on the C++ framework ChimeraTK Application Core. With this close interconnection to the control system it is possible not only to monitor but also to intervene as it is of great importance for supervisory tasks. The core of the tool consists of fault analysis modules ranging from simple ones (e.g., limit checking) to advanced ones (model-based, machine learning, etc.). Within this poster the architecture and the implementation of the trip event logger are presented.  
slides icon Slides THPP4 [7.570 MB]  
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THP09 Smart Video Plug-In System for Beamline Operation at EMBL Hamburg 66
 
  • E.G. Galikeev, C. Blanchet, S. Fiedler, V. Palnati, U. Ristau, D. von Stetten
    EMBL, Hamburg, Germany
 
  Fast data collection, image processing, and analysis of video signals are required by an increasing number of applications at the EMBL beamlines for structural biology at the PETRA III synchrotron in Hamburg, Germany. Consequently, a new Smart Video Plug-in system has been designed in-house to meet the needs by combining video capture, machine learning, and computer vision with online feedback for motion control. The new system is fully integrated into TINE: data acquisition, and experiment control system. In this paper, the architecture of the new video system is described and use cases relevant to beamline operations are presented.  
poster icon Poster THP09 [0.927 MB]  
DOI • reference for this paper ※ doi:10.18429/JACoW-PCaPAC2022-THP09  
About • Received ※ 02 October 2022 — Revised ※ 05 October 2022 — Accepted ※ 17 February 2023 — Issue date ※ 20 February 2023
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FRO21 EPICS IOC and PVs Information Management System for SHINE 107
 
  • H.H. Lv, G.H. Chen, Q.R. Mi, Y.B. Yan
    SSRF, Shanghai, People’s Republic of China
 
  For Shanghai HIgh repetition rate XFEL aNd Extreme light facility(SHINE), EPICS is adopted as standard to build the complex control system which involves hundreds of IOCs and millions of records. Most of IOCs run in industrial control computers as soft IOC. However, with the large amount of PVs, the need has emerged to develop remote tools to monitor all the channels and IOCs. One application backed by MySQL is designed, running periodically to interact with EPICS system where to take data from run-time databases via Channel Access and pvAccess. We embed scripting codes into the IOC startup script to realize that as soon as the IOC starts up, the information of the server’s address, the IOC installation path, and all the records maintained by the IOC will be automatically pushed to the application and then stored in the database. With this necessary information, we could access all the active IOCs and PVs. Another web application is designed to render servers, IOCs and PVs data in MySQL on the web to give us an overall running status of the control system. We also fully consider the modularity and portability for the applications to apply and extend in none-SHINE environments.  
DOI • reference for this paper ※ doi:10.18429/JACoW-PCaPAC2022-FRO21  
About • Received ※ 29 September 2022 — Revised ※ 06 October 2022 — Accepted ※ 17 February 2023 — Issue date ※ 20 February 2023
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FRO22 Data Acquisition Software Pipeline for the Commissioning of the LoKI Small Angle Neutron Scattering Instrument 110
 
  • J.L. Walker, S. Alcock, M.J. Christensen, J.E. Houston, K. Muric, W. Potrzebowski, T.S. Richter
    ESS, Copenhagen, Denmark
  • D. Raspino
    STFC/RAL/ISIS, Chilton, Didcot, Oxon, United Kingdom
 
  The LoKI Small-Angle Neutron Scattering (SANS) instrument will be one of the first instruments to be commissioned at the European Spallation Source (ESS), and will contribute to the early science programme. The detector for the instrument was tested at the ISIS neutron source facility in March of 2022, and this paper outlines the data acquisition software pipeline. It consists of a readout master, an Event Formation Unit (EFU), an instance of Kafka, a NeXus file writer, and, the data reduction software, Scipp. The readout master is responsible for synchronising detector readout timestamps with an external reference, and aggregating those readouts into UDP packets sent to the EFU. The EFU processes the readout data to produce event messages containing a location and time of arrival for each neutron event detected, and acts as a Kafka producer sending event messages to Kafka. The NeXus file writer consists of a Kafka consumer that compiles event messages and other experiment data from a given time interval into a single NeXus file for further analysis. Finally, Scipp is a data reduction python library used to visualise and analyse the experiment data after an experiment is completed.  
slides icon Slides FRO22 [12.942 MB]  
DOI • reference for this paper ※ doi:10.18429/JACoW-PCaPAC2022-FRO22  
About • Received ※ 30 September 2022 — Revised ※ 09 February 2023 — Accepted ※ 17 February 2023 — Issue date ※ 19 February 2023
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FRO23 Experimental Data Collection Standards at SESAME Synchrotron 116
 
  • M.A. Alzubi, A. Abbadi, M. Abdellatief, A. Al-Dalleh, A. Aljadaa, B.R. Aljamal, M.F. Genisel, M. Harfouche, G. Iori, G.S. Kamel, R. Khrais, A. Lausi, S.A. Matalgah, A.S. Mohammad, Y.R. Momani
    SESAME, Allan, Jordan
 
  Experimental data collection is the essential process of acquiring experimental raw data along with its associated metadata from SESAME beamlines. For data collection and processing; scanning modes, data and metadata formats, and data visualisation are only a few aspects in which individual beamlines differ from each other. In addition, the volume of experimental datasets every experimental day might range from a few gigabytes to many terabytes. Herein, the effectiveness of the experiments being conducted at SESAME depends heavily on the efficiency and reliability with which experimental data are collected. Each beamline at SESAME has its own Data Acquisition (DAQ) that ensures that experimental raw data and metadata are not randomly generated and are stored together in a stander and well-defined file formats in compliance with SESAME Experimental Data Management Policy. In this paper, we present the standards and features employed in SESAME’s DAQ systems, as well as the experimental data creation, curation, storage, and accessibility pipeline currently being built for SESAME beamlines.  
slides icon Slides FRO23 [1.460 MB]  
DOI • reference for this paper ※ doi:10.18429/JACoW-PCaPAC2022-FRO23  
About • Received ※ 27 September 2022 — Revised ※ 08 February 2023 — Accepted ※ 15 February 2023 — Issue date ※ 20 February 2023
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