Radio Altimeter Failure Prediction Using Altitude Difference Analytics
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Solution Overview
Problem
Current systems lack the capability to detect and predict radio altimeter failures, leading to potential flight delays, cancellations, and increased maintenance costs due to erroneous altitude readings and unforeseen failures.
Innovation Solution
A data analytics system that calculates a radio altimeter failure indicator by analyzing historical data from multiple radio altimeters, determining differences in altitude values, and evaluating these differences against thresholds to predict potential failures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If radio altimeter systems operate without failure prediction capability, then the system structure remains simple, but flight operations experience delays and cancellations due to unforeseen failures
Solution Approach 1:
The system performs preliminary analysis of altitude data from multiple radio altimeters to calculate failure indicators before actual failures occur. By continuously monitoring and analyzing historical altitude values, the system predicts potential failures in advance, allowing preventive maintenance scheduling that avoids flight delays and cancellations.
Solution Approach 2:
The patent introduces a data analytics system as an intermediary layer between the radio altimeters and flight operations. This intermediary processes altitude data, calculates failure indicators, and provides predictions without requiring direct modification of the radio altimeter hardware, thus adding prediction capability while maintaining relative system simplicity.
2Measurement precision
If multiple radio altimeters are monitored with detailed data analysis, then failure prediction accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The system extracts only the essential features from raw altitude data by calculating mode values and mode value differences. Instead of analyzing all raw altitude measurements in detail, the system extracts the statistically significant differences between altimeter readings, maintaining prediction accuracy while reducing processing time and computational resources.
Solution Approach 2:
The patent transforms raw altitude data into derived parameters such as mode values, mode value differences, and failure indicators. By changing the parameter representation from raw measurements to statistical features, the system achieves accurate failure prediction with reduced computational complexity and faster processing.
Data Source
AI summary
Methods, apparatuses, and systems for predicting radio altimeter failures are provided. An example method may include determining a first plurality of altitude values associated with a first radio altimeter, determining a second plurality of altitude values associated with a second radio altimeter, calculating a first level feature based at least in part on the first plurality of altitude values and the second plurality of altitude values, and determining a radio altimeter failure indicator based at least in part on the first level feature.