Blade Tip Timing Zeroing for Gas Turbine Rotor Monitoring
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Solution Overview
Problem
Existing methods for zeroing blade tip displacement data in gas turbine engines are time-consuming and prone to errors due to the difficulty in identifying and isolating vibration events, especially when small displacements are similar to noise levels, leading to uncertainty in displacement amplitude calculations.
Innovation Solution
A method that measures the actual and predicted time of arrival of rotor features at multiple probes, calculates displacement by subtracting the predicted time multiplied by rotational speed, and separates data into common and unique terms to zero the displacements without manual event identification, allowing for automated and real-time analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual review and visual inspection methods are used to identify and isolate vibration events, then skilled engineers can identify vibration events, but it requires significant time from skilled vibration engineers
Solution Approach 1:
The patent replaces manual visual inspection with an automated signal processing system that uses cross-correlation algorithms to identify vibration events. The system automatically compares measured blade tip displacement data with reference vibration patterns to detect and isolate vibration events without human intervention, thereby eliminating the time consumption of manual review while maintaining identification accuracy.
Solution Approach 2:
The system performs self-service by automatically identifying and isolating vibration events through algorithmic analysis. The cross-correlation method enables the system to autonomously detect vibration events by comparing signal patterns, eliminating the need for skilled engineers to manually review data, thus resolving the contradiction between accuracy and time consumption.
2Extent of automation
If automatic detection methods are used to isolate vibration events, then the process can be automated, but mischaracterising the boundaries of the vibration event causes some of the vibration data to be included in the averages for the portions of the data between the vibration events which consequently skews the averages
Solution Approach 1:
The patent employs feedback through cross-correlation analysis to precisely determine vibration event boundaries. The system continuously compares the measured displacement signal with reference vibration patterns, using the correlation output to accurately identify the start and end points of vibration events. This feedback mechanism ensures that only pure vibration data is isolated for averaging, preventing contamination from non-vibration portions and maintaining measurement precision while achieving full automation.
3Measurement precision
If data averaging technique is applied to isolate vibration events, then vibration events can be characterized, but including vibration data in the averages for portions of the data between vibration events adds uncertainty to reported displacement amplitude
Solution Approach 1:
The patent extracts only the pure vibration event portions from the displacement data using cross-correlation boundary detection. By precisely identifying vibration event start and end points through pattern matching, the system separates vibration data from non-vibration data. This extraction ensures that averaging is performed exclusively on vibration events, eliminating contamination from inter-event portions and thereby reducing uncertainty in displacement amplitude measurements while maintaining characterization capability.
Data Source
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AI summary
A method of zeroing displacement data derived from a rotor (2) having an array of features (4) monitored by an array of stationary timing probes (3). The method comprising steps to calculate the displacement (dj) at each probe (3) for each of at least two measured revolutions from time of arrival measurements. Each displacement (dj) is defined as a sum of a common term (Pcommon) and a unique term (Pj_unique). The set of displacements (dj) is solved for the common term (Pcommon) and the unique terms (Pj_unique). A probe offset (Pj_offset) is calculated from each unique term (Pj_unique). The zeroed displacements (dj) are determined by subtracting the common term (Pcommon) and probe offset (Pj_offset) from the calculated displacements (dj) for each probe (3).