Abstract
A novel fault diagnosis method, named CPS, is proposed based on the combination of CEEMDAN (complete ensemble empirical mode decomposition with adaptive noise), PSM (periodic segment matrix), and SVD (singular value decomposition). Firstly, the collected vibration signals are decomposed into a set of IMFs using CEEMDAN. Secondly, the PSM of the selected IMFs is constructed. Thirdly, singular values are obtained by SVD conducted on the space of PSM. Fourthly, the impulse components are enhanced by the singular value reconstruction with the first maximal singular value. Finally, the squared envelope spectra of the reconstructed signals are used to diagnose the wheelset bearing faults. The effectiveness of the proposed CPS has been verified by simulations and experiments. Compared to the well‐known Hankel‐based SVD, the proposed CPS performs better at extracting the weak periodic impulse responses from the measured signals with strong noise and interferences.
Highlights
A novel fault diagnosis method, named CPS, is proposed based on the combination of CEEMDAN, periodic segment matrix (PSM), and singular value decomposition (SVD)
The collected vibration signals are decomposed into a set of intrinsic mode functions (IMFs) using CEEMDAN
To reduce the adverse influences of mode mixing on extracting fault information, various variations of EMD have been proposed in succession, such as ensemble empirical mode decomposition (EEMD) [13], complementary EEMD (CEEMD) [14], and complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) [15, 16]
Summary
CEEMDAN was further improved to address the presence of residual noise in the modes and the existence of spurious modes [16]. E calculation steps are summarized as follows: Step 1: let k 1 and initialize rk−1 x. I, add the kth mode denoted by Mk(w(i)) decomposed with each w(i) by EMD to rk−1, i.e., x(i) rk−1 + βk-1Mkw(i). Step 3: calculate the first mode of X(i), denoted by M1(X(i)), to obtain the kth residue: rk. Step 4: calculate the kth IMF: IMFk rk−1 − rk. K 1 where rK+1 is the residue of signal x after K IMFs are extracted. The low-amplitude vibration signal is submerged in the IMFs decomposed by CEEMDAN, preventing the fault features from being effectively extracted. Erefore, a method for enhancing periodic impact components in an IMF is expected
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
