Avionics Anomaly Timing Display for Sensor Reliability Decisions
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Solution Overview
Problem
In aircraft systems, determining reliable data sources during anomalies is challenging due to redundant sensors outputting faulty data, leading to potential misidentification of valid data as anomalous and increased pilot stress, which can result in sub-optimal decision-making.
Innovation Solution
A method and system that predict and depict future times when avionics data anomalies will occur, providing uncertainty and animation on display devices, allowing pilots to assess and prepare for anomalies without compromising situational awareness, using time series data and anomaly metric analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If redundant sensors are used to detect anomalies, then reliability of anomaly detection is improved, but difficulty in determining which data source is reliable increases
Solution Approach 1:
The system performs preliminary analysis of sensor data trends before anomalies occur, predicting future anomaly times based on historical patterns. This allows the system to prepare and identify reliable data sources in advance, rather than attempting to determine reliability reactively when anomalies are already present
Solution Approach 2:
The system analyzes multiple parameters and sensors beyond what is minimally required, examining comprehensive data sets including historical trends, environmental conditions, and sensor performance metrics to make more accurate determinations about data source reliability
2Difficulty of detecting and measuring
If logical comparisons are used to identify discrepancies, then anomaly detection capability is improved, but response time available to pilots deteriorates
Solution Approach 1:
The system continuously performs logical comparisons and anomaly detection in the background before pilots need to make decisions. By predicting anomaly times in advance, the system provides early warnings that give pilots adequate time to respond without compromising situational awareness
Solution Approach 2:
The system acts as an intermediary between complex sensor data and pilots, automatically processing and interpreting data comparisons. This mediator function reduces the cognitive burden on pilots while maintaining high anomaly detection capability
3Measurement precision
If unexpected anomaly reports are generated, then anomaly detection accuracy is improved, but pilot decision-making quality deteriorates due to stress
Solution Approach 1:
By predicting anomaly times in advance, the system allows pilots to mentally prepare for upcoming issues. This proactive notification reduces surprise and stress when anomalies occur, enabling more rational decision-making while maintaining high detection accuracy
Solution Approach 2:
The system takes preliminary action to counteract the negative effects of unexpected anomalies by providing advance warning. This allows pilots to prepare countermeasures or contingency plans before the anomaly actually occurs, reducing its disruptive impact
Data Source
AI summary
Methods and systems for depicting avionics data anomalies in an aircraft. Time series data is received from the avionics data source, a future time is predicted when a first anomaly threshold will be crossed based on the time series data, and the future time when the first anomaly threshold will be crossed is depicted on a display device associated with the aircraft.