Pulsation signals analysis of turbocharger turbine blades based on optimal EEMD and TEO

• Autorzy: Wang Fengli

Identyfikatory

DOI

10.2478/pomr-2019-0048

• Języki publikacji: EN

Abstrakty

EN

Turbocharger turbine blades suffer from periodic vibration and flow induced excitation. The blade vibration signal is a typical non-stationary and sometimes nonlinear signal that is often encountered in turbomachinery research and development. An example of such signal is the pulsating pressure and strain signals measured during engine ramp to find the maximum resonance strain or during engine transient mode in applications. As the pulsation signals can come from different disturbance sources, detecting the weak useful signals under a noise background can be difficult. For this type of signals, a novel method based on optimal parameters of Ensemble Empirical Mode Decomposition (EEMD) and Teager Energy Operator (TEO) is proposed. First, an optimization method was designed for adaptive determining appropriate EEMD parameters for the measured vibration signal, so that the significant feature components can be extracted from the pulsating signals. Then Correlation Kurtosis (CK) is employed to select the sensitive Intrinsic Mode Functions (IMFs). In the end, TEO algorithm is applied to the selected sensitive IMF to identify the characteristic frequencies. A case of measured sound signal and strain signal from a turbocharger turbine blade was studied to demonstrate the capabilities of the proposed method.

Słowa kluczowe

EN

urbocharger turbine blades; pulsation signals analysis; ensemble empirical mode decomposition; Teager energy operator; correlation kurtosis

• Wydawca: Gdańsk University of Technology, Faculty of Ocean Engineering & Ship Technology
• Czasopismo: Polish Maritime Research
• Rocznik: 2019
• Tom: nr 3
• Strony: 78--86
• Opis fizyczny: Bibliogr. 21 poz., rys.

Twórcy

autor

Wang Fengli

• College of Marine Engineering Dalian Maritime University Linghai Road No.1, Dalian, Liaoning 116026 Dalian China

Bibliografia

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Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).