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Instantaneous Feature Extraction and Time–Frequency Representation of Rotor Purified Orbit Based on Vold–Kalman Filter

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As a well-known homologous information fusion technology, the full spectrum is widely used in orbit analysis of rotating machinery. However, due to the average effect of the Fourier transform, the… Click to show full abstract

As a well-known homologous information fusion technology, the full spectrum is widely used in orbit analysis of rotating machinery. However, due to the average effect of the Fourier transform, the instantaneous features of the axis orbit cannot be obtained in full spectrum. This limits the application of the full spectrum in a nonstationary vibration analysis. The time–frequency representation (TFR) of axis orbit has been proved to be an effective tool for analyzing nonstationary vibration signals. In this article, a new approach of instantaneous features extraction of harmonic axis orbits is proposed. Furthermore, based on these features, an approach to construct the purified orbit TFR (POTFR) is proposed. First, the estimated speed signal is extracted from the TFR of a single-channel signal by data fitting. Guided by the estimated speed signal, the harmonic components of interest are separated by the Vold–Kalman filter. Furthermore, the parameters of each harmonic instantaneous orbit are calculated from the time domain by using the separated harmonic signals. Based on these parameters, high-resolution POTFRs of all the harmonic orbits are constructed. Finally, the POTFR of the original signal is obtained by combining the POTFRs of all the harmonic components. The proposed approach is illustrated by numerical simulation and is further validated using laboratory experimental signals of oil whip and bistable behavior. The start-up signal from a hydroelectric generating set further demonstrates the superiority of the method.

Keywords: frequency representation; time; vold kalman; purified orbit; time frequency; orbit

Journal Title: IEEE Transactions on Instrumentation and Measurement
Year Published: 2020

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