Shaft Break Detection via Derivative Parameter Space
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Solution Overview
Problem
Current methods for detecting shaft break in gas turbine engines are not accurate or timely, particularly at low engine powers, and struggle to distinguish shaft break events from surge or other events.
Innovation Solution
A method that monitors the derivatives of shaft speeds of different shafts, defines a two-dimensional parameter space with integration regions, and applies specific integration functions to determine when the integration result crosses a predetermined threshold, generating a shaft break signal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional shaft break detection methods are used, then detection is possible, but accuracy and timeliness deteriorate particularly at low engine powers
Solution Approach 1:
The invention changes the parameters used for detection by monitoring derivatives of shaft speeds (first and second parameters) instead of raw shaft speeds alone. This parameter transformation enables accurate shaft break detection even at low engine powers where conventional methods fail, directly resolving the contradiction between detection accuracy and reliability under varying operating conditions.
Solution Approach 2:
The invention introduces a two-dimensional parameter space defined by the first and second parameters (derivatives of shaft speeds), adding a dimensional perspective to the detection process. This dimensional expansion allows the system to distinguish shaft break events from surge events more effectively, improving both accuracy and reliability across all engine power levels.
2Measurement precision
If conventional detection methods are used, then detection is possible, but the ability to distinguish shaft break events from surge events deteriorates
Solution Approach 1:
By defining a two-dimensional parameter space with integration regions, the invention creates additional discriminative dimensions that allow clear separation between shaft break events and surge events. The integration function applied to this two-dimensional space provides a robust mechanism for event differentiation, eliminating false detections while maintaining high detection accuracy.
Solution Approach 2:
The two-dimensional parameter space is segmented into distinct integration regions, each with its own integration function. This segmentation allows the system to handle different event types (shaft break vs. surge) with region-specific processing, improving event differentiation accuracy and preventing harmful false detections.
3Reliability
If robust detection is implemented, then detection reliability improves, but system complexity increases
Solution Approach 1:
The detection system uses a universal two-dimensional parameter space framework with integration functions that can handle multiple event types (shaft break, surge, and other events) through a single unified approach. This multi-functionality achieves robust detection reliability without proportionally increasing system complexity, as the same structural framework processes all event types.
Data Source
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AI summary
A method to detect shaft break that comprises monitoring first and second parameters and defining a two-dimensional parameter space that is a function of the first and second parameters, the two-dimensional parameter space comprises integration regions. The method also comprises defining an integration function for each integration region. For measured values of the first and second parameters, the method determines the applicable integration region and applies the integration function to the first parameter to give an integration result; and then sets a shaft break signal to TRUE when the integration result exceeds a predetermined threshold. The present invention also provides a shaft break detection system.