A Method of Embedded Computer Degradation Trend Prediction
- Resource Type
- Conference
- Authors
- Mao, Y.; Ma, Z.; Gao, S.; Li, L.; Yuan, B.; Chai, B.; He, P.; Liu, X.
- Source
- 2022 5th International Conference on Pattern Recognition and Artificial Intelligence (PRAI) Pattern Recognition and Artificial Intelligence (PRAI), 2022 5th International Conference on. :1338-1343 Aug, 2022
- Subject
- Computing and Processing
Signal Processing and Analysis
Computers
Degradation
Temperature sensors
Temperature measurement
Temperature distribution
Correlation
Prototypes
embedded computer
prognostics health management
degradation trend analysis
acceleration factor
- Language
During the product life cycle, electronic systems in aerospace equipment often experience different working states such as storage, testing, and power-on. It is of great significance for maintenance personnel to monitor the health status of electronic systems in time to study the degradation trend analysis based on key parameters of embedded computers. This paper collects data on key parameters of embedded computers during temperature-accelerated aging and evaluates real-time input data at normal working temperatures. The degradation curve of the component under storage conditions is calculated from the high temperature test data using the acceleration factor. We use the real input data under storage to update the acceleration factor and reasonably estimate its current degradation trend. This approach provides a technical means for the development of a new generation of computer health management.