Sensor-Based Real-Time Condition Monitoring and Three-Level Fault Pre-Warning for Cryogenic Dewar Systems

Cryogenic dewars housing low-noise amplifiers are safety-critical: a slow temperature rise can indicate loss of vacuum or insufficient cooling and may escalate into hard failure within hours to days, yet fixed-threshold monitoring gives too little lead time and no explanation of the alarm cause. This paper proposes a sensor-based real-time condition monitoring and three-level fault pre-warning method, demonstrated on real two-stage temperature and vacuum records from the L, C and Q band dewars of a 26 m radio telescope. Sliding-window smoothing precedes online k-means, which assigns each frame to one of four states (steady, rising, dropping, ambient). In a steady state, an AR(2) model extrapolates the trend, and a finite state machine issues yellow, orange, and red warnings according to the rate of change.The vacuum reading serves as an auxiliary criterion for joint warning. On over 20 million real frames (bad-point rate up to 37.5%), it raises precision—measured as the agreement of the warning frames with the method’s own event list rather than as an independent fault detection accuracy—from 0.0486 to 0.2051 on C and from 0.0009 to 0.2484 on Q in a same-protocol comparison on the calibration (early) segment, not a held-out test. It also lowers the out-of-zone warning-frame fraction, attains a pre-warning window recall of 0.93–1.00, and runs at about 1.8 μs per frame (5.6×105 frames/s), fast enough for real-time embedded use. Continuous monitoring captured only steady or mildly trending segments, with no hard fault triggered.