Cyclostationarity by examples
TL;DR: In this paper, a tutorial on cyclostationarity oriented towards mechanical applications is presented, with 20 examples devoted to illustrating key concepts on actual mechanical signals and demonstrating how cyclostatarity can be taken advantage of in machine diagnostics, identification of mechanical systems and separation of mechanical sources.
About: This article is published in Mechanical Systems and Signal Processing.The article was published on 2009-05-01. It has received 519 citations till now.
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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.
1,858 citations
TL;DR: It is demonstrated that the joint consideration of the infograms significantly extends the domain of applicability of the kurtogram, in particular to situations corrupted with impulsive noise or when the relaxation time of the transients is low as compared to their rate of repetition.
409 citations
TL;DR: In this article, the spectral kurtosis (SK) technique is extended to that of a function of frequency that indicates how the impulsiveness of a signal can be detected and analyzed.
378 citations
TL;DR: In this article, the authors provide a critical review of the predictive health monitoring methods of the entire defect evolution process i.e. wear evolution over the whole lifetime and suggest enhancements for rolling element bearing monitoring.
346 citations
TL;DR: A thorough review of vibration-based bearing and gear health indicators constructed from mechanical signal processing, modeling, and machine learning is presented and provides a basis for predicting the remaining useful life of bearings and gears.
Abstract: Prognostics and health management is an emerging discipline to scientifically manage the health condition of engineering systems and their critical components. It mainly consists of three main aspects: construction of health indicators, remaining useful life prediction, and health management. Construction of health indicators aims to evaluate the system’s current health condition and its critical components. Given the observations of a health indicator, prediction of the remaining useful life is used to infer the time when an engineering systems or a critical component will no longer perform its intended function. Health management involves planning the optimal maintenance schedule according to the system’s current and future health condition, its critical components and the replacement costs. Construction of health indicators is the key to predicting the remaining useful life. Bearings and gears are the most common mechanical components in rotating machines, and their health conditions are of great concern in practice. Because it is difficult to measure and quantify the health conditions of bearings and gears in many cases, numerous vibration-based methods have been proposed to construct bearing and gear health indicators. This paper presents a thorough review of vibration-based bearing and gear health indicators constructed from mechanical signal processing, modeling, and machine learning. This review paper will be helpful for designing further advanced bearing and gear health indicators and provides a basis for predicting the remaining useful life of bearings and gears. Most of the bearing and gear health indicators reviewed in this paper are highly relevant to simulated and experimental run-to-failure data rather than artificially seeded bearing and gear fault data. Finally, some problems in the literature are highlighted and areas for future study are identified.
326 citations
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Book•
01 Jan 1971
TL;DR: A revised and expanded edition of this classic reference/text, covering the latest techniques for the analysis and measurement of stationary and nonstationary random data passing through physical systems, is presented in this article.
Abstract: From the Publisher:
A revised and expanded edition of this classic reference/text, covering the latest techniques for the analysis and measurement of stationary and nonstationary random data passing through physical systems. With more than 100,000 copies in print and six foreign translations, the first edition standardized the methodology in this field. This new edition covers all new procedures developed since 1971 and extends the application of random data analysis to aerospace and automotive research; digital data analysis; dynamic test programs; fluid turbulence analysis; industrial noise control; oceanographic data analysis; system identification problems; and many other fields. Includes new formulas for statistical error analysis of desired estimates, new examples and problem sets.
6,693 citations
TL;DR: It is shown that the cyclostationarity attribute, as it is reflected in the periodicities of (second-order) moments of the signal, can be interpreted in terms of the property that allows generation of spectral lines from the signal by putting it through a (quadratic) nonlinear transformation.
Abstract: It is shown that the cyclostationarity attribute, as it is reflected in the periodicities of (second-order) moments of the signal, can be interpreted in terms of the property that allows generation of spectral lines from the signal by putting it through a (quadratic) nonlinear transformation. The fundamental link between the spectral-line generation property and the statistical property called spectral correlation, which corresponds to the correlation that exists between the random fluctuations of components of the signal residing in distinct spectral bands, is explained. The effects on the spectral-correlation characteristics of some basic signal processing operations, such as filtering, product modulation, and time sampling, are examined. It is shown how to use these results to derive the spectral-correlation characteristics for various types of man-made signals. Some ways of exploiting the inherent spectral redundancy associated with spectral correlation to perform various signal processing tasks involving detection and estimation of highly corrupted man-made signals are described. >
1,012 citations
TL;DR: A concise survey of the literature on cyclostationarity is presented and includes an extensive bibliography and applications of cyclostatedarity in communications, signal processing, and many other research areas are considered.
935 citations