Abstract
Demodulation is one of the most useful techniques for the fault diagnosis of rotating machinery. The commonly used demodulation methods try to select one sensitive sub-band signal that contains the most fault-related components for further analysis. However, a large number of the fault-related components that exist in other sub-bands are ignored in the commonly used envelope demodulation methods. Based on a weighted-empirical mode decomposition (EMD) de-noising technique and time–frequency (TF) impulse envelope analysis, a multi-scale demodulation method is proposed for fault diagnosis. In the proposed method, EMD is first employed to divide the signal into some IMFs (intrinsic mode functions). Then, a new weighted-EMD de-noising technique is presented, and different weights are assigned to IMFs for construction according to their fault-related degrees; thus, the fault-unrelated components are suppressed to improve the signal-to-noise ratio (SNR). After that, continuous wavelet transformation (CWT) is adopted to obtain the time–frequency representation (TFR) of the de-noised signal. Subsequently, the fault-related components in the entire frequency range scale are calculated together, referring to the TF impulse envelope signal. Finally, a fault diagnosis result can be obtained after the fast Fourier transformation of the TF impulse envelope signal. The proposed method and three commonly used methods are applied to the fault diagnosis of a planetary gearbox with a sun gear spalling fault and a fixed shaft gearbox with a crack fault. The results show that the proposed method can effectively detect gear faults and yields better performance than other methods.
Highlights
As one of the most important power transmission systems, gearboxes are widely used in many areas to provide a controlled application of power; e.g., in industrial machinery, ships, helicopters, wind turbines and automobiles [1,2,3]
Wang et al proposed an enhanced Kurtogram method for the fault diagnosis of bearings, where kurtosis values were calculated based on the power spectrum of the envelope of the signals extracted from wavelet packet nodes at different depths; their method was proven to be effective for the detection of various bearing faults [21]
This paper proposed a multi-scale demodulation analysis for the fault diagnosis of a gearbox using a weighted-empirical mode decomposition (EMD) de-noising technique and time–frequency impulse envelope analysis
Summary
As one of the most important power transmission systems, gearboxes are widely used in many areas to provide a controlled application of power; e.g., in industrial machinery, ships, helicopters, wind turbines and automobiles [1,2,3]. Fan et al proposed a new fault detection method that combined envelope analysis and wavelet packet transform, and it was applied to extract the modulating signal and help to detect gear faults in gearboxes at an early stage [14]. Wang et al proposed an enhanced Kurtogram method for the fault diagnosis of bearings, where kurtosis values were calculated based on the power spectrum of the envelope of the signals extracted from wavelet packet nodes at different depths; their method was proven to be effective for the detection of various bearing faults [21].
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