A Spatiotemporal Domain-Coupled Clustering Method for Performance Prediction of Cluster Systems

The performance prediction of the Five-hundred-meter Aperture Spherical radio Telescope (FAST) project represents one of the primary challenges faced by the system. To address the performance prediction issues of the FAST hydraulic actuator cluster system, a spatiotemporal domain-coupled clustering performance prediction method is proposed. By preprocessing data from the FAST health monitoring system, virtual samples constructed from temporal-domain data are integrated with spatial-domain data, thereby resolving the small-sample and even zero-sample issues caused by missing fault data in the FAST hydraulic actuator cluster system. The effectiveness of the spatiotemporal domain-coupled clustering is validated through performance prediction of the hydraulic actuator cluster system. Subsequent optimization of the prediction protocol based on experimental outcomes demonstrated exceptional performance, with 96.8% of actuators achieving prediction accuracies exceeding 99%. This advancement establishes a robust technical foundation for accurate performance prediction in the FAST hydraulic actuator cluster system, thereby enhancing operational reliability and maintenance efficiency.