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@InProceedings{azzopardi:icalepcs2019-mopha010, author = {G. Azzopardi and A. Muscat and S. Redaelli and B. Salvachua and G. Valentino}, title = {{Automatic Beam Loss Threshold Selection for LHC Collimator Alignment}}, booktitle = {Proc. ICALEPCS'19}, pages = {208--213}, paper = {MOPHA010}, language = {english}, keywords = {alignment, collimation, beam-losses, detector, software}, venue = {New York, NY, USA}, series = {International Conference on Accelerator and Large Experimental Physics Control Systems}, number = {17}, publisher = {JACoW Publishing, Geneva, Switzerland}, month = {08}, year = {2020}, issn = {2226-0358}, isbn = {978-3-95450-209-7}, doi = {10.18429/JACoW-ICALEPCS2019-MOPHA010}, url = {https://jacow.org/icalepcs2019/papers/mopha010.pdf}, note = {https://doi.org/10.18429/JACoW-ICALEPCS2019-MOPHA010}, abstract = {The collimation system used in the Large Hadron Collider at CERN is positioned around the beam with a hierarchy that protects sensitive equipment from unavoidable beam losses. The collimator settings are determined using a beam-based alignment technique, where collimator jaws are moved towards the beam until the beam losses exceed a predefined threshold. This threshold needs to be updated dynamically, corresponding to the changes in the beam losses. The current method for aligning collimators is semi-automated requiring a collimation expert to monitor the loss signals and continuously select and update the threshold accordingly. The human element in this procedure is a major bottleneck for speeding up the alignment. This paper therefore proposes a method to fully automate this threshold selection. A data set was formed from previous alignment campaigns and analyzed to define an algorithm that produced results consistent with the user selections. In over 90% of the cases the difference between the two was negligible and the algorithm presented in this study was used for collimator alignments throughout 2018.}, }