Journal ArticleDOI
Application of CSA-VMD and optimal scale morphological slice bispectrum in enhancing outer race fault detection of rolling element bearings
Xiaoan Yan,Minping Jia +1 more
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TLDR
A modified method known as cuckoo search algorithm-based variational mode decomposition (CSA-VMD) is proposed, which can decompose adaptively a multi-component signal into a superposition of sub-signals termed as intrinsic mode function (IMF) by means of parameter optimization.About:
This article is published in Mechanical Systems and Signal Processing.The article was published on 2019-05-01. It has received 128 citations till now. The article focuses on the topics: Fault detection and isolation & Fault (power engineering).read more
Citations
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Journal ArticleDOI
Multi-step wind speed forecasting based on hybrid multi-stage decomposition model and long short-term memory neural network
Sinvaldo Rodrigues Moreno,Sinvaldo Rodrigues Moreno,Ramon Gomes da Silva,Viviana Cocco Mariani,Viviana Cocco Mariani,Leandro dos Santos Coelho,Leandro dos Santos Coelho +6 more
TL;DR: The proposed combination of two signal decomposition strategies, known as variational mode decomposition (VMD) and singular spectral analysis (SSA) with modulation signal theory are proposed, which indicate that ensembles learning framework are robust and reliable to applications in wind speed forecasting task.
Journal ArticleDOI
A fault information-guided variational mode decomposition (FIVMD) method for rolling element bearings diagnosis
TL;DR: Successful fault diagnosis of rolling element bearings under complicated operating conditions, including early bearing fault signals in run-to-failure test datasets, signals with impulsive noise and planet bearing signals, demonstrates that the proposed FIVMD is a superior approach in extracting weak bearing repetitive transients.
Journal ArticleDOI
Incipient fault diagnosis of rolling bearings based on adaptive variational mode decomposition and Teager energy operator
TL;DR: The proposed adaptive variational mode decomposition and Teager energy operator method (AVMD-TEO) can effectively reduce signal noise and extract incipient fault feature of rolling bearings.
Journal ArticleDOI
A rotating machinery fault diagnosis method based on multi-scale dimensionless indicators and random forests
TL;DR: Results indicate that the MSDI can effectively solve the deficiency of the traditional dimensionless indicator, and has stronger distinguishing ability for the fault types.
Journal ArticleDOI
A fault information-guided variational mode decomposition (FIVMD) method for rolling element bearings diagnosis
TL;DR: In this article , a fault information-guided variational mode decomposition (FIVMD) method is proposed for extracting the weak bearing repetitive transient, and two nested statistical models based on the fault cyclic information, incorporated with the statistical threshold at a specific significance level, are used to approximately determine the mode number.
References
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Journal ArticleDOI
Variational Mode Decomposition
TL;DR: This work proposes an entirely non-recursive variational mode decomposition model, where the modes are extracted concurrently and is a generalization of the classic Wiener filter into multiple, adaptive bands.
Book
Rolling Bearing Analysis
Tedric A. Harris,W. J. Crecelius +1 more
TL;DR: Rolling bearing types and applications Rolling Bearing Macrogeometry Interference Fitting and Clearance Bearing Loads and Speeds Ball and Roller Loads Contact Stress and Deformation Distribution of Internal Loading in Statically Loaded Bearingings Internal Speeds and Motions Distribution of internal Loading in High Speed Bearing Deflection, Preloading, and Stiffness Statically Indeterminate Shaft - Bearing Systems Lubricant Films in Rolling Element - Raceway Contacts Friction in Fluid-Lubricated Rolling Element- RacewayContacts friction in Rolling Bearingings Rolling Bearing Temperatures Bearing
Journal ArticleDOI
Rolling element bearing diagnostics—A tutorial
Robert B. Randall,Jérôme Antoni +1 more
TL;DR: This tutorial is intended to guide the reader in the diagnostic analysis of acceleration signals from rolling element bearings, in particular in the presence of strong masking signals from other machine components such as gears.
Journal ArticleDOI
A review on empirical mode decomposition in fault diagnosis of rotating machinery
TL;DR: This paper attempts to survey and summarize the recent research and development of EMD in fault diagnosis of rotating machinery, providing comprehensive references for researchers concerning with this topic and helping them identify further research topics.
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Rolling element bearing diagnostics using the Case Western Reserve University data: A benchmark study
Wade A. Smith,Robert B. Randall +1 more
TL;DR: Though intended primarily as a benchmark to aid in testing new diagnostic algorithms, it is also hoped that much of the discussion will have broader applicability to other bearing diagnostics cases.