State-based prognostics with similarity enhancement for CT X-ray tubes using operational logs
Changjun Chen1, Xiangjie Wang1, Linze Qian2
1Department of Clinical Engineering, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
Biomedizinische Technik. Biomedical Engineering
|July 12, 2026
Summary
This study introduces a novel method for estimating the remaining useful life (RUL) of CT X-ray tubes. The approach accurately predicts tube degradation without needing predefined failure points, enhancing medical equipment maintenance.
Area of Science:
- Medical Imaging Technology
- Prognostics and Health Management
Background:
- Computed Tomography (CT) X-ray tubes are critical, high-cost components with limited operational lifespans.
- Accurate estimation of remaining useful life (RUL) is essential for effective maintenance and operational planning.
Purpose of the Study:
- To develop a method for estimating CT X-ray tube RUL.
- To enable RUL prediction without requiring a preset failure threshold or prior knowledge of tube life.
Main Methods:
- Selected CT scan types with stable tube current distribution.
- Developed a composite metric for a candidate health indicator (HI).
- Normalized HI to a percentage health indicator (PHI) and applied state-based prognostics with similarity enhancement for RUL estimation.
Main Results:
- Validated the method using real-world CT tube log data with leave-one-out cross-validation.
- Achieved optimal prediction performance and enabled cross-tube RUL estimation.
- Demonstrated that predictions reflect actual tube degradation without a failure threshold.
Conclusions:
- The proposed approach offers an effective and practical framework for CT X-ray tube RUL estimation.
- Shows significant potential for practical application in medical equipment maintenance strategies.
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