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On-line partial discharge (PD) testing has been used for decades to help maintenance personnel detect rotating machine stator winding insulation problems at an early stage and thus optimally plan any required maintenance. Specifically, the test can find loose, overheated, and contaminated windings, well before these problems lead to failure. The test has also found use in determining the effectiveness of any repair work.The widespread application of on-line PD testing has enabled the accumulation over the past 20 years of a database with, currently, approximately 700,000 test results. This proposed contribution presents the basics of on-line data collection, including the implementation of noise rejection algorithms and possible methods in improvements in interpreting test results. One case study describing application of on-line partial discharge testing on a hydro generator will be presented.

This white-paper expresses common requirements of Research Communities seeking to leverage Identity Federation for Authentication and Authorisation. Recommendations are made to Stakeholders to guide the future evolution of Federated Identity Management in a direction that better satisfies research use cases. The authors represent research communities, Research Services, Infrastructures, Identity Federations and Interfederations, with a joint motivation to ease collaboration for distributed researchers. The content has been edited collaboratively by the Federated Identity Management for Research (FIM4R) Community, with input sought at conferences and meetings in Europe, Asia and North America., The authors also acknowledge the support and collaboration of many other colleagues in their respective institutes, research communities and IT Infrastructures, together with the funding received by these from many different sources. These include but are not limited to the following: (i) The Worldwide LHC Computing Grid (WLCG) project is a global collaboration of more than 170 computing centres in 43 countries, linking up national and international grid infrastructures. Funding is acknowledged from many national funding bodies and we acknowledge the support of several operational infrastructures including EGI, OSG and NDGF/NeIC. (ii) EGI acknowledges the funding and support received from the European Commission and the many National Grid Initiatives and other members. EOSC-hub receives funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 777536. (iii) The work leading to these results has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No. 730941 (AARC2). (iv) Work on the development of ESGF's identity management system has been supported by The UK Natural Environment Research Council and funding from the European Union's Seventh Framework Programme for research, technological development and demonstration through projects IS-ENES (grant agreement no 228203) and IS-ENES2 (grant agreement no 312979). (v) Ludek Matyska and Michal Prochazka acknowledge funding from the RI ELIXIR CZ project funded by MEYS Czech Republic No. LM2015047. (vi) Scott Koranda acknowledges support provided by the United States National Science Foundation under Grant No. PHY-1700765. (vii) GÉANT Association on behalf of the GN4 Phase 2 project (GN4-2).The research leading to these results has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No. 731122(GN4-2). (viii) ELIXIR acknowledges support from Research Infrastructure programme of Horizon 2020 grant No 676559 EXCELERATE. (ix) CORBEL life science cluster acknowledges support from Horizon 2020 research and innovation programme under grant agreement No 654248. (x) Mirjam van Daalen acknowledges that the research leading to this result has been supported by the project CALIPSOplus under the Grant Agreement 730872 from the EU Framework Programme for Research and Innovation HORIZON 2020. (xi) EISCAT is an international association supported by research organisations in China (CRIRP), Finland (SA), Japan (NIPR), Norway (NFR), Sweden (VR), and the United Kingdom (NERC).

High-speed X-ray imaging applications play a crucial role for non-destructive investigations of the dynamics in material science and biology. On-line data analysis is necessary for quality assurance and data-driven feedback, leading to a more efficent use of a beam time and increased data quality. In this article we present a smart camera platform with embedded Field Programmable Gate Array (FPGA) processing that is able to stream and process data continuously in real-time. The setup consists of a Complementary Metal-Oxide-Semiconductor (CMOS) sensor, an FPGA readout card, and a readout computer. It is seamlessly integrated in a new custom experiment control system called Concert that provides a more efficient way of operating a beamline by integrating device control, experiment process control, and data analysis. The potential of the embedded processing is demonstrated by implementing an image-based trigger. It records the temporal evolution of physical events with increased speed while maintaining the full field of view. The complete data acquisition system, with Concert and the smart camera platform was successfully integrated and used for fast X-ray imaging experiments at KIT’s synchrotron radiation facility ANKA.

Research Infrastructures increasingly use national and global “Research and Education” (R&E) authentication federations to provide access to their services. Studies in the AARC project have shown that research communities connect to the R&E federation using an ‘SP-IdP proxy’. The use of a proxy in itself poses policy challenges. As seen by the R&E federations, the SP-IdP proxy hides all of the research services. Home organisations and R&E federations see just a single service provider, even if the services behind it are provided in hundreds of different administrative domains. Building on the Security for Collaboration among Infrastructures (SCI) framework, the “Security Networked-Community Trust-framework for Federated Identity” (Snctfi) proposes a policy framework that allows determination of the ‘quality’ of such SP-IdP proxies and the research services behind them. “Snctfi” allows comparison between proxies, and it allows a scalable way to negotiate and filter based on such policies. We present here version 1 of the “Snctfi” trust framework.

X-ray computed tomography (CT) is a method for non-destructive investigation. Three-dimensional images of internal structure can be reconstructed using a two-dimensional detector. The poly-chromatic high density photon flux in the modern synchrotron light sources offers hard X-ray imaging with a spatio-temporal resolution up to the µm-µs range. Existing indirect X-ray image detectors can be adapted for fast image acquisition by employing CMOS-based digital high speed camera. In this paper, we propose a high-speed visible light camera based on commercial CMOS sensor with embedded processing implemented in FPGA. This platform has been used to develop a novel architecture for a self-event trigger. This feature is able to increase the original frame rate of the CMOS sensor and reduce the amount of the received data. Thanks to a low noise design, high frame rate (kilohertz range) and high speed data transfer, this camera can be employed in modern synchrotron ultra-fast X-ray radiography and computed tomography. The camera setup is accomplished by high-throughput Linux drivers and a seamless integration in our GPU computing framework. Selected applications from life sciences and materials research underline the high potential of this high-speed camera in a hard X-ray micro-imaging approach.

High-speed X-ray imaging applications such as radiography and tomography play a crucial role for non-destructive investigations in material and biology sciences. For data-intensive applications, on-line analysis of the data is necessary for initial quality assurance and data-driven feedback. In this article we will present a new smart camera platform, with embedded FPGA processing that is able to stream and process data continuously in real-time. It is used in the new imaging beamline IMAGE, in ANKA. The new smart camera platform consists of a CMOS sensor, an FPGA readout card connected with a high speed PCIe interface to the GPU-based readout computer. It is tightly coupled to a newly implemented control system, called Concert. Concert enables efficient operation of the beamline by integrating devices and experiment process control, as well as data analysis. A key feature of smart cameras is embedded image processing. In this article we will demonstrate the potential of this approach with the implementation of an image-based self-event trigger. The algorithm automatically restricts the readout to selected regions with changed content. Application dependent trigger parameters are hidden by our control system which sets them automatically according to experiment requirements and conditions.