Abstract
Gearboxes are widely used in drive systems of rotating machinery. The health status of gearboxes considerably influences the normal and reliable operation of rotating machinery. When a gearbox experiences tooth failure, a vibration signal with impulse features is excited. However, these impulse features tend to be relatively weak and difficult to extract. To solve this problem, a novel approach for gearbox fault feature extraction and fault diagnosis based on improved variational mode extraction (VME) is proposed. Since the initial value of the desired mode center frequency and the value of the penalty parameter in VME must be assigned, a short-time Fourier transform (STFT) was performed, and a new index, the standard deviation of differential values of envelope maxima positions (SDE), is proposed. The feasibility and effectiveness of the proposed approach was verified by a simulation signal and two datasets associated with a gearbox test bench. The results demonstrate that the VME-based approach outperforms the variational mode decomposition (VMD) approach.
Highlights
Gearboxes are widely used in rotating machinery, such as wind turbines, nuclear power units, high-speed rail, and new energy vehicles, and their performance influences the normal and reliable operation of rotating machinery
The findings indicate that the initial ω d value, 2π·1490 rad/s, selected from the short-time Fourier transform (STFT) spectrum is the optimal value that results in a minimum SDE index value 27.1316
The performance of variational mode extraction (VME) is highly robust to the initial value of the desired mode center frequency and the penalty parameter
Summary
Gearboxes are widely used in rotating machinery, such as wind turbines, nuclear power units, high-speed rail, and new energy vehicles, and their performance influences the normal and reliable operation of rotating machinery. The penalty parameter value must not be excessively large; otherwise, the desired mode may lose useful information Considering these aspects, this paper proposes an improved VME method, in which the initial value of the desired mode center frequency is selected by the STFT spectrum, and Sensors 2022, 22, 1779 the optimal value of the penalty parameter is determined using a novel index: the standard deviation of differential values of envelope maxima positions (SDE).
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