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Oblique projection pre-processing and TLS application for diagnosing rotor bar defects by improving power spectrum estimation

Abstract : Diagnosing defects on rotating machines can be reached by several angles. When dealing with asynchronous motor drive, such physical elements rotate that a natural angle for treating the healthiness of the motor can be obtained by the use of spectral analysis tools. It is now stated that electrical or mechanical defects, which appear periodically as well, can be retrieved by analyzing the amplitude of particular frequencies inside an estimated power spectrum. When dealing with broken rotor bars detection it is essential to accurately localize the frequencies related to the slip inside the power spectrum. The diagnosis is thereafter made by indicators given with respect to their power. For actual low level of load operations, the supply frequency generally masks the frequencies which could be exploited for indicators. Therefore, we propose to cancel, as well as possible, the contribution of this supply frequency to develop the useful and closely components. The resolution should be very thin for the components to be estimated. In consequence, we use a prior-knowledge subspace-based frequency estimator, already developed in the literature, we complete with an Oblique Projection coupled with a Total Least Squares solution for estimating the power of the resulting estimated frequencies. Finally, we show by means of a real application how it contributes to improve the power spectrum estimation when compared to the FFT or periodogram-based analysis and how the aforementioned power spectrum makes the diagnosis indicator of rotor bars efficient.
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Contributor : Guillaume Bouleux Connect in order to contact the contributor
Submitted on : Friday, April 14, 2017 - 2:19:59 PM
Last modification on : Tuesday, April 21, 2020 - 1:29:33 AM
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Guillaume Bouleux. Oblique projection pre-processing and TLS application for diagnosing rotor bar defects by improving power spectrum estimation. Mechanical Systems and Signal Processing, Elsevier, 2013, 41, pp.301 - 312. ⟨10.1016/j.ymssp.2013.06.018⟩. ⟨hal-01508672⟩

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