IBIC2016 - List of Authors (Pedersen, S.B.)

Paper	Title	Page
MOPG39	Upgrade of the LHC Bunch by Bunch Intensity Measurement Acquisition System	135
	D. Belohrad, D. Esperante Pereira, J. Kral, S.B. Pedersen CERN, Geneva, Switzerland
	The fast beam intensity measurement systems for the LHC currently use an analogue signal processing chain to provide the charge information for individual bunches. This limits the possibility to use higher level correction algorithms to remove systematic measurement errors coming from the beam current transformer and the associated analogue electronics chain. In addition, the current measurement system requires individual settings for different types of beams, implying the need for continuous tuning during LHC operation. Using modern technology, the analogue measurement chain can be replaced by an entirely digital acquisition system, even in a case of the short, pulsed signals produced by the LHC beams. This paper discusses the implementation of the new digital acquisition system and the calculations required to reconstruct the individual LHC bunch intensities, along with the presentation of results from actual beam measurements.
DOI •	reference for this paper ※ DOI:10.18429/JACoW-IBIC2016-MOPG39
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TUPG45	The CERN Beam Instrumentation Group Offline Analysis Framework	449
	B. Kolad, J-J. Gras, S. Jackson, S.B. Pedersen CERN, Geneva, Switzerland
	Beam instrumentation systems at CERN require periodic verifications of both their state and condition. Presently, experts have no generic solution to observe and analyse an instrument's condition and as a result, many ad-hoc Python scripts have been developed to extract historical data from CERN's logging service. Clearly, ad-hoc developments are not desirable for medium/long term maintenance reasons and therefore a generic solution has been developed. In this paper we present the Offline Analysis Framework (OAF), used for automatic report generation based on data from the central logging service. OAF is a Java / Python based tool which allows generic analysis of any instrument's data extracted from the database. In addition to the generic analysis, advanced analysis can also be performed by providing custom Python code. This paper will explain the steps of the analysis, its scope and present the kind of reports that are generated and how instrumentation experts can benefit from it. We will also show how this approach simplifies debugging, allows code re-use and optimises database and CPU resource usage.
	Poster TUPG45 [1.623 MB]
DOI •	reference for this paper ※ DOI:10.18429/JACoW-IBIC2016-TUPG45
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Page

Upgrade of the LHC Bunch by Bunch Intensity Measurement Acquisition System

135

D. Belohrad, D. Esperante Pereira, J. Kral, S.B. Pedersen
CERN, Geneva, Switzerland

The fast beam intensity measurement systems for the LHC currently use an analogue signal processing chain to provide the charge information for individual bunches. This limits the possibility to use higher level correction algorithms to remove systematic measurement errors coming from the beam current transformer and the associated analogue electronics chain. In addition, the current measurement system requires individual settings for different types of beams, implying the need for continuous tuning during LHC operation. Using modern technology, the analogue measurement chain can be replaced by an entirely digital acquisition system, even in a case of the short, pulsed signals produced by the LHC beams. This paper discusses the implementation of the new digital acquisition system and the calculations required to reconstruct the individual LHC bunch intensities, along with the presentation of results from actual beam measurements.

DOI •

reference for this paper ※ DOI:10.18429/JACoW-IBIC2016-MOPG39

Export •

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

TUPG45

The CERN Beam Instrumentation Group Offline Analysis Framework

449

B. Kolad, J-J. Gras, S. Jackson, S.B. Pedersen
CERN, Geneva, Switzerland

Beam instrumentation systems at CERN require periodic verifications of both their state and condition. Presently, experts have no generic solution to observe and analyse an instrument's condition and as a result, many ad-hoc Python scripts have been developed to extract historical data from CERN's logging service. Clearly, ad-hoc developments are not desirable for medium/long term maintenance reasons and therefore a generic solution has been developed. In this paper we present the Offline Analysis Framework (OAF), used for automatic report generation based on data from the central logging service. OAF is a Java / Python based tool which allows generic analysis of any instrument's data extracted from the database. In addition to the generic analysis, advanced analysis can also be performed by providing custom Python code. This paper will explain the steps of the analysis, its scope and present the kind of reports that are generated and how instrumentation experts can benefit from it. We will also show how this approach simplifies debugging, allows code re-use and optimises database and CPU resource usage.

Poster TUPG45 [1.623 MB]

DOI •

reference for this paper ※ DOI:10.18429/JACoW-IBIC2016-TUPG45

Export •

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