Engine Health Prediction Using Adaptive Performance Curves
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Solution Overview
Problem
Current engine health monitoring systems, such as Power Assurance Checks (PACs), require prolonged stable operation, introduce human error, and fail to accurately predict engine performance at varying load levels, making them burdensome for flight crews and limited in accuracy.
Innovation Solution
A system and method that collects engine data to determine health by receiving operating information, selecting a performance curve, and using curve-fitting processes to create an engine health model, allowing for accurate health assessment without requiring prolonged stable operation or high power levels, and reducing crew burden.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Power Assurance Checks are performed using traditional methods requiring stable steady-state operation, then measurement precision is improved, but loss of time increases and ease of operation deteriorates
Solution Approach 1:
The system performs preliminary data collection and curve fitting during normal operation to establish baseline performance characteristics before actual health assessment is needed. This allows the system to have prediction models ready in advance, eliminating the need for prolonged stable operation at the time of assessment.
Solution Approach 2:
The patent replaces the mechanical requirement for prolonged stable steady-state operation with a computational system that uses adaptive algorithms and curve fitting to analyze engine data. This substitution allows health assessment during transient operation without requiring the traditional mechanical stability conditions.
2Loss of time
If manual Power Assurance Checks are performed to reduce loss of time, then ease of operation improves, but measurement precision deteriorates due to human error
Solution Approach 1:
The system performs self-assessment by automatically collecting engine data, fitting performance curves, and determining health status without requiring flight crew intervention. The engine health monitoring system serves itself by using its own operational data to assess its condition, eliminating human error while maintaining speed.
Solution Approach 2:
The system implements continuous feedback by monitoring engine parameters, comparing actual performance against fitted curves, and automatically updating health assessments. This closed-loop feedback mechanism replaces manual checking with automated real-time monitoring that is both fast and accurate.
3Measurement precision
If Power Assurance Checks are performed at high engine loads to improve measurement precision, then measurement precision improves, but ease of operation deteriorates due to difficult operating conditions
Solution Approach 1:
The system transitions from static assessment requiring fixed high-load conditions to dynamic assessment that adapts to varying operating conditions. The adaptive algorithm continuously adjusts the performance curves based on current engine operation, allowing accurate health assessment across the entire operating range without requiring specific high-load conditions.
Solution Approach 2:
The patent changes the assessment parameters from requiring fixed high-load conditions to using variable parameters that adapt to current operating conditions. By using adaptive curve fitting that works across different load levels, the system eliminates the need to operate at difficult-to-acquire high loads while maintaining or improving measurement precision.
4Device complexity
If traditional PAC methods are used to reduce device complexity, then device complexity decreases, but reliability deteriorates due to assumptions about consistent performance across load levels
Solution Approach 1:
The system segments the engine performance assessment into multiple load-level specific evaluations rather than using a single blanket assessment. By fitting separate performance curves for different operating conditions and combining the results, the system achieves high reliability without excessive complexity, as each segment can be processed independently using standard algorithms.
Data Source
AI summary
A system and algorithm-based method of determining engine health and assuring available propulsion power based on historical data reflecting the individual engine's unique performance “fingerprint.”