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Title: Development of blade tip timing data analysis techniques
Author: Carrington, Ian B.
ISNI:       0000 0001 3521 5800
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2002
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All turbomachines experience vibration from a variety of sources. Resonance may occur that subjects one or more blades to maximum stress conditions. Blade tip-timing (BTT) is a emergent, alternative blade stress measurement technology that is non-intrusive and noncontacting, yet delivers data on all blades in a rotor stage. By measuring blade tip passing times at a number of sensors mounted externally on the rotor's casing, processing and analysis of this data yields resonance frequencies or Engine Orders, and tip amplitudes. This study sought to advance Rolls-Royce's strategy for BTT by improving its data processing and analysis capabilities in two areas: 1. Data analysis of blades undergoing synchronous resonance, by the development of: • A multiple degrees-of-freedom blade tip displacement simulator, created to provide representative synchronous data under controlled conditions. • The formulation of a number of approaches new to BIT data analysis and their evaluation and comparison using the above simulator: three variations of an Autoregressive (AR) approach an Eigen decomposition technique and a matrix Determinant method. • An experimental Rig, designed and constructed to provide real BTT data at low cost, with which to test and begin validation of the best analysis methods. 2. The productionisation ofBTT at Rolls-Royce, which will be enhanced by: • A fast ellipse-fitting algorithm for the Two Parameter Plot (2PP) analysis method. • An ellipse-fitting Goodness-of-Fit Factor to aid analysis automation. • Cross-correlation data analysis that detects resonance behaviour automatically. This work makes the following recommendations: 1. One of the three AR techniques is robust and reliable enough for industrial use. 2. The fast ellipse-fitting algorithm be written into an industrial 2PP analysis package. 3. Trial Cross-correlation analysis on industrial data to establish its reliability further. 4. Replace optical 'spot' probes with 'line' probes to reduce measurement uncertainties. 5. Increase the industrial BTT system capacity to allow connection of up to eight probes.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available