Data engineering for the electrical quality assurance of the LHC - a preliminary study

Matej Mertik and Knud Dahlerup-Petersen

International Journal of Data Mining, Modelling and Management, 2017, vol. 9, issue 1, 65-78

Abstract: In this paper, we present a case study of the development of a scientific tool for the data analysis and engineering of large Hadron collider (LHC) commissioning data when implementing electrical quality assurance on the LHC machine. We present the development process of the data models and a prototype application developed on these data models. We explain the iterative process when searching for appropriate models and we explain the preliminary research on feature extraction of the signal necessary for building the models. We conclude the paper with remarks on the preliminary work, developed prototype and its functionalities and we discuss the future development plan.

Keywords: data mining; data engineering; data visualisation; knowledge visualisation; large Hadron collider; LHC; electrical quality assurance; ELQA; feature extraction; data analysis; data modelling. (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=82553 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijdmmm:v:9:y:2017:i:1:p:65-78

Access Statistics for this article

More articles in International Journal of Data Mining, Modelling and Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().