SMART X-RAY-BEAM POSITION MONITOR SYSTEM USING ARTIFICIAL-INTELLIGENCE METHODS FOR THE ADVANCED PHOTON SOURCE INSERTION-DEVICE BEAMLINES

At the Advanced Photon Source (APS), each insertion-device (ID) beamli ne front end has two X-ray beam position monitors (XBPMs) to monitor t he X-ray beam position for both vertical and horizontal directions. Pe rformance challenges for a conventional photoemission-type XBPM during operations are contamination of the signal from the neighbouring bend ing-magnet sources and the sensitivity of the XBPM to the insertion-de vice gap variations Problems are exacerbated because users change the ID gap during their operations, and hence the percentage level of the contamination in the front-end XBPM signals varies. A smart XBPM syste m with a high-speed digital signal processor has been built at the Adv anced Photon Source for the LD beamline front ends. The new version of the software, which uses an artificial-intelligence method, provides a self-learning and self-calibration capability to the smart XBPM syst em. The structure of and recent test results with the system are prese nted in this paper.