Machine Learning Used in BPM Displacement Prediction at HLS II
Year: 2024
Type: conference-paper
Abstract: Beam orbit stability is a crucial indicator that can be used to evaluate the performance of a synchrotron radiation source. It can be improved through precise orbit measurement with beam position monitors (BPMs) and appropriate orbit feedback. The move-ment of BPMs directly affects the measurement of the beam orbit and indirectly affects the beam orbit through orbit feedback (OFB) system. Two sets of BPM displacement measurement system were estab-lished at Hefei Light Source II (HLS II) storage ring and some machine learning work was carried out on the system.
Source: JACOW
Authors: Sun,Bao-gen, Wang,Chuhan, Wang,Dongyu, Lan,Jinkai, Ma,MingDong, Zhou,Tianyu
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W6887978012
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