State-based prognostics with similarity enhancement for CT X-ray tubes using operational logs

OBJECTIVES: The tube is a core component of the CT system and is characterized by high cost and limited lifespan. This study aims to develop a method for estimating the remaining useful life (RUL) of CT X-ray tubes without requiring a preset failure threshold or prior knowledge of tube life. METHODS: To reduce the impact of varying scan conditions, different scan types are first analyzed, and the one with the most stable tube current distribution is selected. Then, a composite metric is applied to degradation parameters to obtain a candidate health indicator (HI). Next, the candidate HI is normalized using the training set and transformed into a percentage health indicator (PHI) to represent tube degradation. Finally, a state-based prognostics with similarity enhancement is applied to the PHI to estimate RUL. RESULTS: The proposed method is evaluated using real tube log data under leave-one-out cross-validation. The results demonstrate that it achieves optimal prediction performance and enables cross-tube RUL estimation. Moreover, the prediction results can reflect the actual degradation progress of the tube without requiring a preset failure threshold. CONCLUSIONS: The proposed approach provides an effective and practical framework for CT X-ray tube RUL estimation, demonstrating good potential for practical medical equipment maintenance.