Guide Vane Sensor Selection for Engine Stall and Surge Avoidance
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Solution Overview
Problem
Existing turbine engine control systems face challenges in ensuring redundancy and accuracy of guide vane feedback to prevent engine stalls and surges, which can be exacerbated by sensor degradation or damage in harsh environments, and adding more sensors imposes size, weight, and power penalties.
Innovation Solution
A controller system that compares feedback from multiple guide vane sensors, performs a ranked comparison of turbine performance data during finite intervals using each sensor, and selects the most reliable sensor based on performance metrics to ensure accurate guide vane positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple VGV sensors are used to ensure redundancy and accuracy of guide vane feedback, then reliability is improved, but device complexity increases
Solution Approach 1:
The system implements feedback by continuously monitoring VGV position through multiple sensors and using engine performance data to validate sensor readings. The controller compares feedback from multiple sensors and selects the most reliable reading based on engine behavior correlation, ensuring accurate guide vane position information without requiring additional hardware beyond the existing sensor infrastructure.
Solution Approach 2:
The system changes parameters by evaluating engine performance metrics (such as compressor inlet temperature, turbine power output, and fuel flow) to determine which sensor reading correlates best with actual engine behavior. This parameter-based validation allows the system to dynamically select the most reliable sensor feedback without physical redundancy, resolving the contradiction between reliability and complexity.
2Measurement precision
If sensor degradation or damage is accounted for in harsh environments, then measurement precision is maintained, but device complexity increases
Solution Approach 1:
The system uses engine performance feedback to continuously validate sensor readings. By monitoring parameters such as compressor inlet temperature, turbine power output, and fuel flow, the system can detect when a sensor reading diverges from expected engine behavior, indicating degradation or damage. This feedback mechanism maintains measurement precision without requiring complex additional monitoring hardware.
Solution Approach 2:
The system performs self-validation by using its existing engine performance monitoring capabilities to assess sensor health. The controller compares sensor readings against expected engine behavior derived from other monitored parameters, allowing the system to self-diagnose sensor degradation and switch to alternative readings or diagnostic modes without external intervention or additional complexity.
3Reliability
If additional sensors are added to improve redundancy, then reliability is improved, but SWAP penalties increase
Solution Approach 1:
The system creates virtual redundancy by using software-based validation and cross-correlation of existing sensor data with engine performance parameters. Instead of physically copying sensors (adding hardware redundancy), the system creates multiple validation pathways through software algorithms that assess sensor reliability based on engine behavior, achieving redundancy without additional weight.
Solution Approach 2:
The system makes existing engine monitoring parameters serve multiple functions: they simultaneously control engine operation and validate sensor readings. Parameters such as compressor inlet temperature and turbine power output are already being monitored for engine control purposes; the invention repurposes these same parameters for sensor validation, achieving redundancy without additional sensors or weight.
Data Source
AI summary
A method for managing mismatches in feedback from guide vane sensors of a turbine engine with variable guide vanes includes selectively muting individual feedback channels and obtaining time series turbine performance data of the turbine engine associated with individual feedback channels. The feedback channel of the guide vane sensor associated with the best performing time series performance data can be selected as sole feedback channel following detection of a mismatch condition.