Preprint Article Version 1 This version is not peer-reviewed

Evaluation of the ContinuousWavelet Transform for Detection of Single-Point Rub in Aeroderivative Gas Turbines with Accelerometers

Version 1 : Received: 10 May 2018 / Approved: 10 May 2018 / Online: 10 May 2018 (16:10:11 CEST)

A peer-reviewed article of this Preprint also exists.

Silva, A.; Zarzo, A.; Munoz-Guijosa, J.M.; Miniello, F. Evaluation of the Continuous Wavelet Transform for Detection of Single-Point Rub in Aeroderivative Gas Turbines with Accelerometers. Sensors 2018, 18, 1931. Silva, A.; Zarzo, A.; Munoz-Guijosa, J.M.; Miniello, F. Evaluation of the Continuous Wavelet Transform for Detection of Single-Point Rub in Aeroderivative Gas Turbines with Accelerometers. Sensors 2018, 18, 1931.

Journal reference: Sensors 2018, 18, 1931
DOI: 10.3390/s18061931

Abstract

A common fault in turbomachinery is rotor--casing rub. Shaft vibration, measured with proximity probes, is the most powerful indicator of rotor-stator rub. However, in machines such as aeroderivative turbines, with increasing industrial relevance in power generation, constructive reasons prevent the use of those sensors, being only acceleration signals at selected casing locations available. This implies several shortcomings in the characterization of the machinery condition, associated with a lower information content about the machine dynamics. In this work we evaluate the performance of the Continuous Wavelet Transform to isolate the accelerometer signal features that characterize rotor-casing rub in an aeroderivative turbine. The evaluation is carried out on a novel rotor model of a rotor flexible casing system. Due to damped transients and other short-lived features that rub induces in the signals, the Continuous Wavelet Transform proves being more effective than both Fourier and Cepstrum Analysis. This creates the chance for enabling early fault diagnosis of rub before it may cause machine shutdown or damage.

Subject Areas

machine fault diagnosis; rotordynamics; rub; aeroderivative turbines; accelerometers; early fault detection; fourier analysis; real cepstrum; continuous wavelet transform

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