Speaker
Description
The Proton Synchrotron Booster (PSB) accelerates protons with a fundamental radiofrequency (RF) system operating at the revolution frequency, with additional voltage at its second harmonic. Both RF systems are operated in counter-phase for bunch lengthening to reduce space charge effects. To maximise the bunch length , the phase of the voltage at the second harmonic must follow the beam synchronous phase. Imperfect phase and delay compensation in the RF signal path combined with strong beam loading at high beam intensity, impose a need to manually correct the phase for each beam type throughout the cycle. This correction is straightforward but time consuming. To accelerate the process, an automatic phase corrector to estimate the relative phase error of the second harmonic from the measured beam profile based on a convolutional neural network with attention mechanisms has been developed. The network was trained on simulated and noise-enhanced data before being validated with beam in the PSB. The contribution will present the design, training, optimisation and validation of this tool.
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