A method for multi-harmonic vibration analysis of turbomachinery blades using Blade Tip-Timing and clearance sensor waveforms and optimization techniques

•Novel concept of investigating blade vibration on the basis of sensor waveforms.•Mitigation of the under-sampling problem with BTT.•Modeling of a capacitive sensor based on experimental waveform data.•Asynchronous and synchronous single-harmonic and multi-harmonic vibration studies.•Sensitivity stu...

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Veröffentlicht in:Mechanical systems and signal processing 2020-08, Vol.142, p.106741, Article 106741
Hauptverfasser: Heller, D., Sever, I.A., Schwingshackl, C.W.
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Sprache:eng
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Zusammenfassung:•Novel concept of investigating blade vibration on the basis of sensor waveforms.•Mitigation of the under-sampling problem with BTT.•Modeling of a capacitive sensor based on experimental waveform data.•Asynchronous and synchronous single-harmonic and multi-harmonic vibration studies.•Sensitivity study of the error susceptibility of the methodology. A novel concept of investigating blade vibration in turbomachinery is presented on the basis of Blade Tip-Timing (BTT) and clearance sensor waveformanalysis methods (BLASMA), with which vibration parameters are determined by global optimization. It is shown that the modulation of the sensor output by blade vibration can offer additional information compared with under-sampled time-of-arrival (TOA) data from traditional BTT applications. The sensor data can not only improve the validity of statements on blade vibration but also lessen the dependence on contact-based strain gauges measurements to produce reference data. A study was conducted to evaluate the merit of sensor waveform analysis with regard to determining asynchronous and synchronous single-harmonic and multi-harmonic blade vibration parameters. At first, waveforms were recorded with capacitive sensors during an experiment conducted on a research compressor. The experimentally measured waveforms were afterwards replicated in a simulator for imitating passing events of rotating and vibrating blades along a single virtual capacitive sensor. Finally, vibration properties, such as amplitudes, frequencies, and phases, are extracted from these waveforms with the help of global optimization methods. An investigation into the error proneness of the methodology is attached.
ISSN:0888-3270
1096-1216
DOI:10.1016/j.ymssp.2020.106741