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Description
Real-time bunch-by-bunch monitoring of transverse position and longitudinal phase has become increasingly important for the stable operation of storage ring light sources and for accelerator physics studies. This paper presents a real-time three-dimensional bunch-by-bunch position measurement system based on machine learning. The system eliminates the need for sampling delay adjustment and avoids complex front-end circuitry by directly digitizing BPM electrode signals with high-speed ADCs at a sampling rate of five times the storage ring RF frequency. By deploying neural network models within the FPGA, the system simultaneously achieves real-time measurement of the transverse position and longitudinal phase with low latency. Beam experiments were conducted at Shanghai Synchrotron Radiation Facility (SSRF) to validate the system’s phase measurement capability. The results demonstrate a bunch-by-bunch phase resolution of 0.4ps while maintaining a measurement latency within 1µs.
| Paper status | Resubmitted proceeding files received and assigned to an editor. Rejected. |
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