Proceedings of the 18th International Conference on Accelerator and Large Experimental Physics Control Systems
International Conference on Accelerator and Large Experimental Physics Control Systems, Shanghai, China, 14-22 October 2021
The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Laboratory is a CW recirculating linac that utilizes over 400 superconducting radio-frequency (SRF) cavities to accelerate electrons up to 12 GeV through 5-passes. Recent work has shown that, given RF signals from a cavity during a fault as input, machine learning approaches can accurately classify the fault type. In this paper we report on initial results of predicting a fault onset using only data prior to the failure event. A data set was constructed using time-series data immediately before a fault (’unstable’) and 1.5 seconds prior to a fault (’stable’) gathered from over 5,000 saved fault events. The data was used to train a binary classifier. The results gave key insights into the behavior of several fault types and provided motivation to investigate whether data prior to a failure event could also predict the type of fault. We discuss our method using a sliding window approach and report on initial results. Recent modifications to the low-level RF control system will provide access to streaming signals and we outline a path forward for leveraging deep learning on streaming data
Original Publication Citation
Vidyaratne, L. S., Carpenter, A., Iftekharuddin, K., Rahman, M. M., Suleiman, R., Tennant, C., & Turner, D. L. (2021) Initial studies of cavity fault prediction at Jefferson Laboratory. In K. Furukawa, Y. Yan, Y. Leng, Z. Chen, Schaa, V.R.W. (Eds.), Proceedings of the 18th International Conference on Accelerator and Large Experimental Physics Control Systems (pp. 700-704). JACoW Publishing. https://doi.org/10.18429/JACoW-ICALEPCS2021-WEPV025
Vidyaratne, L.S.; Carpenter, A.; Suleiman, R.; Tennant, C.; Turner, D.; Iftekharuddin, Khan; and Rahman, Md. Monibor, "Initial Studies of Cavity Fault Prediction at Jefferson Laboratory" (2021). Electrical & Computer Engineering Faculty Publications. 316.