Journal ArticleDOI
A comparison of cepstral editing methods as signal pre-processing techniques for vibration-based bearing fault detection
TLDR
In this paper, a pre-whitening technique was proposed to group the deterministic multi-harmonic signal content in a cepstral peak at the corresponding quefrency, making it more suitable for removing the discrete frequency peaks.About:
This article is published in Mechanical Systems and Signal Processing.The article was published on 2017-07-01. It has received 74 citations till now. The article focuses on the topics: Cepstrum & Mel-frequency cepstrum.read more
Citations
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Journal ArticleDOI
Research on Remaining Useful Life Prediction of Rolling Element Bearings Based on Time-Varying Kalman Filter
TL;DR: A new method for RUL prediction of bearings based on time-varying Kalman filter, which can automatically match different degradation stages of bearings and effectively realize the prediction of RUL is proposed.
Journal ArticleDOI
Blind filters based on envelope spectrum sparsity indicators for bearing and gear vibration-based condition monitoring
TL;DR: The proposed approach is a simple yet effective way of tracking faults with a cyclostationary signature and key in the iterative optimization procedure is the usage of the Rayleigh quotient to update the filter coefficients.
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A review of operational modal analysis techniques for in-service modal identification
TL;DR: Operational modal analysis techniques OMA and ISMA are reviewed with their development over the years and their pros and cons discussed.
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Semi-automated diagnosis of bearing faults based on a hidden Markov model of the vibration signals
TL;DR: A semi-automated method that requires the setting of only one parameter, rooted on a probabilistic model, in the form of a mixture of Gaussians, endowed with a hidden variable that indicates the occurrence of impacts that is shown to be optimal for detection in the Neyman-Pearson sense.
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Vibration Analysis for Machine Monitoring and Diagnosis: A Systematic Review
TL;DR: A systematic review of up-to-date vibration analysis for machine monitoring and diagnosis is presented in this article, which involves data acquisition (instrument applied such as analyzer and sensors), feature extraction, and fault recognition techniques using artificial intelligence (AI).
References
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Journal ArticleDOI
Ideal spatial adaptation by wavelet shrinkage
TL;DR: In this article, the authors developed a spatially adaptive method, RiskShrink, which works by shrinkage of empirical wavelet coefficients, and achieved a performance within a factor log 2 n of the ideal performance of piecewise polynomial and variable-knot spline methods.
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Suppression of acoustic noise in speech using spectral subtraction
TL;DR: A stand-alone noise suppression algorithm that resynthesizes a speech waveform and can be used as a pre-processor to narrow-band voice communications systems, speech recognition systems, or speaker authentication systems.
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The Measurement of Power Spectra
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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.
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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.