Infrared Detector Cooler Predictive Maintenance by Refrigerating Time Drift
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Solution Overview
Problem
Conventional detector coolers in optronics systems are fragile, heterogeneous, and costly, with maintenance limited to detecting breakdowns after they occur, leading to unavailability and high maintenance costs, and there is a need for a system that can anticipate malfunctions without increasing bulk.
Innovation Solution
Implementing a predictive maintenance system that monitors the state of health of the cooler-detector by measuring the drift in refrigerating time, using a processing card to calculate the trend of refrigerating time based on 'on-off' cycles and storing aggregated data to predict potential breakdowns, allowing for self-adaptive behavior and minimal memory usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If predictive maintenance monitoring is implemented to detect breakdowns early, then reliability is improved, but device complexity increases
Solution Approach 1:
The detector cooler system performs self-diagnosis by automatically monitoring its own refrigerating time and comparing it against stored reference values. The system autonomously detects deviations indicating potential failures without requiring external monitoring equipment, thereby improving reliability while avoiding additional system complexity.
Solution Approach 2:
The system implements feedback by continuously measuring the actual refrigerating time, comparing it with reference values stored in memory, and using this comparison to predict potential failures. This closed-loop feedback mechanism enables early detection of degradation trends without adding complex external monitoring infrastructure.
2Measurement precision
If detailed temperature measurements and TMF data are stored for analysis, then measurement precision is improved, but the volume of storage required increases
Solution Approach 1:
The system extracts and stores only the essential reference refrigerating time values in memory, rather than storing complete temperature measurement datasets. This selective extraction approach maintains the precision needed for TMF calculation while dramatically reducing the storage volume required for maintenance monitoring.
Solution Approach 2:
The system performs partial data retention by storing only the critical reference TMF values needed for comparison, rather than preserving all raw temperature data. This partial action approach provides sufficient measurement precision for failure prediction while minimizing memory consumption.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables early detection of potential breakdowns, reduces maintenance costs, enhances operational performance, and increases autonomy by minimizing energy consumption while providing better control over the detector cooler.
Implementation Method 1
a cooling machine 3 which uses, for example, helium and supplies the cryostat 2 with the refrigeration needed to bring its temperature (usually lower its temperature) from an ambient temperature to the operating temperature
Implementation Method 2
a sensor 8 for measuring the temperature Td of the detector supplied by a sensor 8
Implementation Method 3
an IR detector 1 placed in a vacuum chamber (cryostat 2) which maintains the temperature of this chamber at an operating temperature of the detector
Data Source
AI summary
The invention relates to an optronics system equipped with: a detector cooler having a cooling machine, a cryostat, an IR detector placed in the cryostat, and a sensor for measuring the temperature TD of the detector; and a processing card which includes means for servocontrolling the cooling machine according to the temperature TD. The system includes a sensor for sensing the system's internal temperature TS, and the processing card includes means for calculating: the refrigerating time (TMF) based on the temperatures TD and TS, on each “on-off” cycle of the detector cooler, the trend of the drift in the refrigerating time TMF, as a function of the number of “on-off” cycles of the detector cooler, a number of “on-off” cycles of the detector cooler before breakdown as a function of said trend of the drift of the TMF, and means for storing data used in said calculations; these data are aggregated data and not the measurements of temperatures TD and TS, nor said TMFs, in order to limit the size of the storage means.