Invention:
This invention is a prognostics and health management (PHM) test and validation platform named ORACLE. The ORACLE emulates the occurrence of environmental changes and generates a log file to allow for training and subsequent deep learning-based anomaly detection frameworks for monitoring space habitat health. ORACLE uses multi-layer feedforward networks or other deep learning approaches to detect anomalies. The ultimate goal is to use the measured “biometric” changes in each crew member as a supplementary indicator to detect degradation in the space habitat environment and associated habitat subsystems.
This invention has the potential to detect anomalies in sensor data early on. Moreover, this invention provides a test and validation platform to test, validate, and improve anomaly detection schemes for sensor data. ORACLE is agnostic to the source of the sensor data.
Background:
Space habitats must be autonomously operated due to the lack of a permanent occupancy and to constantly ensure the health and safety of individuals residing aboard. The general idea is to use the crew health status as an integrated contributor to other PHM capabilities already implemented on associated space habitat subsystems. The availability and compactness of ECG, blood oxygenation, ocular structure, and vision performance monitoring equipment – ranging from devices having a form-factor of a wristwatch to smartphone-based examination equipment – lend themselves to be ideal in environments where self-diagnostics and payload considerations are vital to mission success.
Applications:
- Habitat monitoring and anomaly detection
- Prognostics and health management
- Artificial intelligence
- Wearable sensors
Advantages:
- Early detection
- Predictability
