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MD3343 - Fully-Automatic Parallel Collimation Alignment using Machine Learning
The collimation system protects the LHC and its sensitive equipment form unavoidable beam losses. Collimators are set up in the form of a hierarchy which is established using a very precise alignment of all the collimators with respect to the beam. In the past years collimators were aligned using a...
Autores principales: | , , |
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Lenguaje: | eng |
Publicado: |
2018
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Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2647213 |
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author | Azzopardi, Gabriella Valentino, Gianluca Salvachua Ferrando, Belen Maria |
author_facet | Azzopardi, Gabriella Valentino, Gianluca Salvachua Ferrando, Belen Maria |
author_sort | Azzopardi, Gabriella |
collection | CERN |
description | The collimation system protects the LHC and its sensitive equipment form unavoidable beam losses. Collimators are set up in the form of a hierarchy which is established using a very precise alignment of all the collimators with respect to the beam. In the past years collimators were aligned using a semi-automatic approach whereby collimation experts manually control the alignment of both beams in parallel. During commissioning 2018, the first version of the fully-automatic software was tested. The first version of this software did not account for crosstalk between the beams, therefore the two beams had to be aligned sequentially. After commissioning, a crosstalk analysis model was developed and integrated into the fully-automatic software. The new parallel software was tested during this MD and managed to successfully align both beams in parallel at injection for the first time. |
id | cern-2647213 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2018 |
record_format | invenio |
spelling | cern-26472132019-09-30T06:29:59Zhttp://cds.cern.ch/record/2647213engAzzopardi, GabriellaValentino, GianlucaSalvachua Ferrando, Belen MariaMD3343 - Fully-Automatic Parallel Collimation Alignment using Machine Learning Accelerators and Storage RingsThe collimation system protects the LHC and its sensitive equipment form unavoidable beam losses. Collimators are set up in the form of a hierarchy which is established using a very precise alignment of all the collimators with respect to the beam. In the past years collimators were aligned using a semi-automatic approach whereby collimation experts manually control the alignment of both beams in parallel. During commissioning 2018, the first version of the fully-automatic software was tested. The first version of this software did not account for crosstalk between the beams, therefore the two beams had to be aligned sequentially. After commissioning, a crosstalk analysis model was developed and integrated into the fully-automatic software. The new parallel software was tested during this MD and managed to successfully align both beams in parallel at injection for the first time. CERN-ACC-NOTE-2018-0071oai:cds.cern.ch:26472132018-09-13 |
spellingShingle | Accelerators and Storage Rings Azzopardi, Gabriella Valentino, Gianluca Salvachua Ferrando, Belen Maria MD3343 - Fully-Automatic Parallel Collimation Alignment using Machine Learning |
title | MD3343 - Fully-Automatic Parallel Collimation Alignment using Machine Learning |
title_full | MD3343 - Fully-Automatic Parallel Collimation Alignment using Machine Learning |
title_fullStr | MD3343 - Fully-Automatic Parallel Collimation Alignment using Machine Learning |
title_full_unstemmed | MD3343 - Fully-Automatic Parallel Collimation Alignment using Machine Learning |
title_short | MD3343 - Fully-Automatic Parallel Collimation Alignment using Machine Learning |
title_sort | md3343 - fully-automatic parallel collimation alignment using machine learning |
topic | Accelerators and Storage Rings |
url | http://cds.cern.ch/record/2647213 |
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