Abstract
Order tracking has been widely used to diagnose failures of variable speed rotating machines. The performance of the TOT (Time-Frequency Domain Tacholess Order Tracking) methods is based on the correct separation of the target component strictly related to the shaft rotation frequency. Currently, most of the methods have focused on obtaining the instantaneous frequency with accuracy. In this paper, a new TOT method has been proposed that combines the inverse short-time Fourier transform (ISTFT) with singular value decomposition (SVD). The target component closely related to the shaft rotation frequency is selected and filtered approximately in the time-frequency domain. Hence, the ISTFT is adopted to reverse the target component into the time domain. Next, SVD is used to refine the roughly filtered target component. Finally, the phase of the refined signal is extracted to resample the original signal. The performance of the method was tested using real vibration signals collected from a large-scale test rig of a high-speed train traction system.
Highlights
Fault diagnosis of rotating machines is very important for the safe and economical operation of the machine, but in the field of fault diagnosis of rotating machines, it is easy to encounter a problem which is the variation of the rotation speed
The rest of the document is organized as follows: Section 2 illustrates the fundamentals of singular value decomposition (SVD); Section 3 explores the effect of relative frequency ratio on SVD performance; Section 4 explores the effect of noise on SVD-based phase extraction; Section 5 shows the process of the new method; Section 6 tests the performance of the new method using real vibration signals
− τ SVD using a different number of rows of phase of the sum of the first two sub-signals obtained the Hankel matrix shown in Figure is a slight between the actual unwrapped
Summary
Fault diagnosis of rotating machines is very important for the safe and economical operation of the machine, but in the field of fault diagnosis of rotating machines, it is easy to encounter a problem which is the variation of the rotation speed. In the field of time domain filtering, Bonnardot et al proposed the idea of using the gear meshing signal to perform the TOT operation [6]. Combet et al proposed an automatic way to select the optimal gear meshing harmonic for TOT This method is only useful for low speed variation. Zhao et al proposed the generalized Fourier transform method, which transforms the selected harmonic into a line parallel to the time axis and uses bandpass filtering to separate the component [7]. A new TOT method of time-frequency filtering based on ISTFT and SVD has been proposed. The processing of the time-frequency domain filtering is an approximate operation, and the refinement process is performed by SVD. The rest of the document is organized as follows: Section 2 illustrates the fundamentals of SVD; Section 3 explores the effect of relative frequency ratio on SVD performance; Section 4 explores the effect of noise on SVD-based phase extraction; Section 5 shows the process of the new method; Section 6 tests the performance of the new method using real vibration signals
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