THE RELATIONSHIP BETWEEN SPECTRAL CORRELATION AND ENVELOPE ANALYSIS IN THE DIAGNOSTICS OF BEARING FAULTS AND OTHER CYCLOSTATIONARY MACHINE SIGNALS
Identifieur interne : 00B954 ( Main/Curation ); précédent : 00B953; suivant : 00B955THE RELATIONSHIP BETWEEN SPECTRAL CORRELATION AND ENVELOPE ANALYSIS IN THE DIAGNOSTICS OF BEARING FAULTS AND OTHER CYCLOSTATIONARY MACHINE SIGNALS
Auteurs : R. B. Randall [Australie] ; J. Antoni [France] ; S. Chobsaard [Thaïlande]Source :
- Mechanical Systems and Signal Processing [ 0888-3270 ] ; 2001.
Descripteurs français
- Pascal (Inist)
English descriptors
- KwdEn :
- Academic press, Additive background noise, Aforementioned solutions, Aliasing, Amplitude modulation, Analytic signal, Autocovariance function, Central time, Classical envelope analysis, Cyclic, Cyclic frequencies, Cyclic frequency, Cyclostationarity, Cyclostationary, Cyclostationary signals, Defect, Defect detection, Demodulated signal, Density function, Deterministic part, Digitised signal, Discrete spectrum, Element bearings, Envelope analysis, Fault diagnostic, Fault signals, Figure displays, Fourier, Fourier series, Fourier transformation, Frequency domain, Gaussian probability density function, Gear, Inner race, Inner race fault, Lter, Ltering, Machine signals, Measurement method, Mechanical systems, Monitoring, More detail, Next section, Non stationary process, Other hand, Other words, Outer race, Outer race fault, Point process, Previous paragraph, Randall, Recent years, Rolling bearing, Same parameters, Same result, Same time, Second order, Shaft, Shaft speed, Shaft speeds, Signal envelope, Signal processing, Spectral, Spectral analysis, Spectral band, Spectral correlation, Spectral correlation analysis, Spectral density, Squared, Squared envelope, Squared envelope analysis, Squared magnitude, Squared magnitude signal, Standard deviation, Stationary process, Statistical analysis, Statistical model, Statistical properties, Stochastic, Stochastic part, Stochastic process, System processing, Time signal, Useful information, Vibration, Vibration signal, Vibration signals.
- Teeft :
- Academic press, Additive background noise, Aforementioned solutions, Aliasing, Amplitude modulation, Analytic signal, Autocovariance function, Central time, Classical envelope analysis, Cyclic, Cyclic frequencies, Cyclic frequency, Cyclostationary, Cyclostationary signals, Defect, Demodulated signal, Density function, Deterministic part, Digitised signal, Discrete spectrum, Element bearings, Envelope analysis, Fault signals, Figure displays, Fourier, Fourier series, Frequency domain, Gaussian probability density function, Inner race, Inner race fault, Lter, Ltering, Machine signals, Mechanical systems, More detail, Next section, Other hand, Other words, Outer race, Outer race fault, Point process, Previous paragraph, Randall, Recent years, Same parameters, Same result, Same time, Second order, Shaft speed, Shaft speeds, Signal processing, Spectral, Spectral band, Spectral correlation, Spectral correlation analysis, Spectral density, Squared, Squared envelope, Squared envelope analysis, Squared magnitude, Squared magnitude signal, Standard deviation, Stationary process, Statistical model, Statistical properties, Stochastic, Stochastic part, Stochastic process, System processing, Time signal, Useful information, Vibration, Vibration signal, Vibration signals.
Abstract
Abstract: In recent years there has been an increasing interest in applying cyclostationary analysis to the diagnostics of machine vibration signals. This is because some machine signals, while being almost periodic, are not exactly phase-locked to shaft speeds, and thus even after compensation for speed fluctuation cannot be extracted by synchronous averaging. Typical examples are the combustion events in IC engines, which vary from cycle to cycle, and impulsive signals from faults in rolling element bearings, which are affected by minor but randomly varying slip. Two main tools for the analysis of cyclostationary signals are the two-dimensional autocorrelation function vs central time on the one axis and time displacement around the central time on the other, and its two-dimensional Fourier transform known as the spectral correlation. The latter can be quite complex to interpret, so some authors have suggested integrating it over all frequencies to obtain a Fourier series spectrumvs cyclic frequency. In this paper, it is shown that this gives the same result as a Fourier transform of the average squared envelope of the signal, which is much easier to obtain directly. Not only that, envelope analysis has long been used in the diagnostics of rolling element bearing signals, and some of the experience gained can be carried over to spectral correlation analysis. There is a possibility that the full spectral correlation may still give some advantage in distinguishing between modulation effects due to gear rotations and bearing inner race rotations (even at the same speed) by virtue of the different amounts of randomness associated with each.
Url:
DOI: 10.1006/mssp.2001.1415
Links toward previous steps (curation, corpus...)
- to stream Istex, to step Corpus: Pour aller vers cette notice dans l'étape Curation :000048
- to stream Istex, to step Curation: Pour aller vers cette notice dans l'étape Curation :000048
- to stream Istex, to step Checkpoint: Pour aller vers cette notice dans l'étape Curation :001D58
- to stream Main, to step Merge: Pour aller vers cette notice dans l'étape Curation :00C799
- to stream PascalFrancis, to step Corpus: Pour aller vers cette notice dans l'étape Curation :005A26
- to stream PascalFrancis, to step Curation: Pour aller vers cette notice dans l'étape Curation :000713
- to stream PascalFrancis, to step Checkpoint: Pour aller vers cette notice dans l'étape Curation :005649
- to stream Main, to step Merge: Pour aller vers cette notice dans l'étape Curation :00C994
Links to Exploration step
ISTEX:027C3B100069021CBCA7E9B8B13DE3F9CCCAB141Le document en format XML
<record><TEI wicri:istexFullTextTei="biblStruct"><teiHeader><fileDesc><titleStmt><title xml:lang="en">THE RELATIONSHIP BETWEEN SPECTRAL CORRELATION AND ENVELOPE ANALYSIS IN THE DIAGNOSTICS OF BEARING FAULTS AND OTHER CYCLOSTATIONARY MACHINE SIGNALS</title><author><name sortKey="Randall, R B" sort="Randall, R B" uniqKey="Randall R" first="R. B." last="Randall">R. B. Randall</name></author><author><name sortKey="Antoni, J" sort="Antoni, J" uniqKey="Antoni J" first="J." last="Antoni">J. Antoni</name></author><author><name sortKey="Chobsaard, S" sort="Chobsaard, S" uniqKey="Chobsaard S" first="S." last="Chobsaard">S. Chobsaard</name></author></titleStmt><publicationStmt><idno type="wicri:source">ISTEX</idno><idno type="RBID">ISTEX:027C3B100069021CBCA7E9B8B13DE3F9CCCAB141</idno><date when="2001" year="2001">2001</date><idno type="doi">10.1006/mssp.2001.1415</idno><idno type="url">https://api.istex.fr/document/027C3B100069021CBCA7E9B8B13DE3F9CCCAB141/fulltext/pdf</idno><idno type="wicri:Area/Istex/Corpus">000048</idno><idno type="wicri:explorRef" wicri:stream="Istex" wicri:step="Corpus" wicri:corpus="ISTEX">000048</idno><idno type="wicri:Area/Istex/Curation">000048</idno><idno type="wicri:Area/Istex/Checkpoint">001D58</idno><idno type="wicri:explorRef" wicri:stream="Istex" wicri:step="Checkpoint">001D58</idno><idno type="wicri:doubleKey">0888-3270:2001:Randall R:the:relationship:between</idno><idno type="wicri:Area/Main/Merge">00C799</idno><idno type="wicri:source">INIST</idno><idno type="RBID">Pascal:02-0056686</idno><idno type="wicri:Area/PascalFrancis/Corpus">005A26</idno><idno type="wicri:Area/PascalFrancis/Curation">000713</idno><idno type="wicri:Area/PascalFrancis/Checkpoint">005649</idno><idno type="wicri:explorRef" wicri:stream="PascalFrancis" wicri:step="Checkpoint">005649</idno><idno type="wicri:doubleKey">0888-3270:2001:Randall R:the:relationship:between</idno><idno type="wicri:Area/Main/Merge">00C994</idno><idno type="wicri:Area/Main/Curation">00B954</idno></publicationStmt><sourceDesc><biblStruct><analytic><title level="a" type="main" xml:lang="en">THE RELATIONSHIP BETWEEN SPECTRAL CORRELATION AND ENVELOPE ANALYSIS IN THE DIAGNOSTICS OF BEARING FAULTS AND OTHER CYCLOSTATIONARY MACHINE SIGNALS</title><author><name sortKey="Randall, R B" sort="Randall, R B" uniqKey="Randall R" first="R. B." last="Randall">R. B. Randall</name><affiliation wicri:level="1"><country xml:lang="fr">Australie</country><wicri:regionArea>School of Mechanical and Manufacturing Engineering, The University of New South Wales, Sydney, 2052</wicri:regionArea><wicri:noRegion>2052</wicri:noRegion></affiliation></author><author><name sortKey="Antoni, J" sort="Antoni, J" uniqKey="Antoni J" first="J." last="Antoni">J. Antoni</name><affiliation wicri:level="3"><country xml:lang="fr">France</country><wicri:regionArea>Laboratoire d'Analyse des Signaux et des Processus Industriels (LASPI), IUT de Roanne, 42334, Roanne</wicri:regionArea><placeName><region type="region" nuts="2">Auvergne-Rhône-Alpes</region><region type="old region" nuts="2">Rhône-Alpes</region><settlement type="city">Roanne</settlement></placeName></affiliation></author><author><name sortKey="Chobsaard, S" sort="Chobsaard, S" uniqKey="Chobsaard S" first="S." last="Chobsaard">S. Chobsaard</name><affiliation wicri:level="1"><country xml:lang="fr">Thaïlande</country><wicri:regionArea>Department of Engineering Development, Royal Thai Naval Dockyard</wicri:regionArea><wicri:noRegion>Royal Thai Naval Dockyard</wicri:noRegion></affiliation></author></analytic><monogr></monogr><series><title level="j">Mechanical Systems and Signal Processing</title><title level="j" type="abbrev">YMSSP</title><idno type="ISSN">0888-3270</idno><imprint><publisher>ELSEVIER</publisher><date type="published" when="2001">2001</date><biblScope unit="volume">15</biblScope><biblScope unit="issue">5</biblScope><biblScope unit="page" from="945">945</biblScope><biblScope unit="page" to="962">962</biblScope></imprint><idno type="ISSN">0888-3270</idno></series></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0888-3270</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Academic press</term><term>Additive background noise</term><term>Aforementioned solutions</term><term>Aliasing</term><term>Amplitude modulation</term><term>Analytic signal</term><term>Autocovariance function</term><term>Central time</term><term>Classical envelope analysis</term><term>Cyclic</term><term>Cyclic frequencies</term><term>Cyclic frequency</term><term>Cyclostationarity</term><term>Cyclostationary</term><term>Cyclostationary signals</term><term>Defect</term><term>Defect detection</term><term>Demodulated signal</term><term>Density function</term><term>Deterministic part</term><term>Digitised signal</term><term>Discrete spectrum</term><term>Element bearings</term><term>Envelope analysis</term><term>Fault diagnostic</term><term>Fault signals</term><term>Figure displays</term><term>Fourier</term><term>Fourier series</term><term>Fourier transformation</term><term>Frequency domain</term><term>Gaussian probability density function</term><term>Gear</term><term>Inner race</term><term>Inner race fault</term><term>Lter</term><term>Ltering</term><term>Machine signals</term><term>Measurement method</term><term>Mechanical systems</term><term>Monitoring</term><term>More detail</term><term>Next section</term><term>Non stationary process</term><term>Other hand</term><term>Other words</term><term>Outer race</term><term>Outer race fault</term><term>Point process</term><term>Previous paragraph</term><term>Randall</term><term>Recent years</term><term>Rolling bearing</term><term>Same parameters</term><term>Same result</term><term>Same time</term><term>Second order</term><term>Shaft</term><term>Shaft speed</term><term>Shaft speeds</term><term>Signal envelope</term><term>Signal processing</term><term>Spectral</term><term>Spectral analysis</term><term>Spectral band</term><term>Spectral correlation</term><term>Spectral correlation analysis</term><term>Spectral density</term><term>Squared</term><term>Squared envelope</term><term>Squared envelope analysis</term><term>Squared magnitude</term><term>Squared magnitude signal</term><term>Standard deviation</term><term>Stationary process</term><term>Statistical analysis</term><term>Statistical model</term><term>Statistical properties</term><term>Stochastic</term><term>Stochastic part</term><term>Stochastic process</term><term>System processing</term><term>Time signal</term><term>Useful information</term><term>Vibration</term><term>Vibration signal</term><term>Vibration signals</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>4680</term><term>Analyse spectrale</term><term>Analyse statistique</term><term>Arbre transmission</term><term>Cyclostationnarité</term><term>Diagnostic panne</term><term>Détection défaut</term><term>Engrenage</term><term>Enveloppe signal</term><term>Monitorage</term><term>Méthode mesure</term><term>Palier roulement</term><term>Processus non stationnaire</term><term>Traitement signal</term><term>Transformation Fourier</term><term>Vibration</term></keywords><keywords scheme="Teeft" xml:lang="en"><term>Academic press</term><term>Additive background noise</term><term>Aforementioned solutions</term><term>Aliasing</term><term>Amplitude modulation</term><term>Analytic signal</term><term>Autocovariance function</term><term>Central time</term><term>Classical envelope analysis</term><term>Cyclic</term><term>Cyclic frequencies</term><term>Cyclic frequency</term><term>Cyclostationary</term><term>Cyclostationary signals</term><term>Defect</term><term>Demodulated signal</term><term>Density function</term><term>Deterministic part</term><term>Digitised signal</term><term>Discrete spectrum</term><term>Element bearings</term><term>Envelope analysis</term><term>Fault signals</term><term>Figure displays</term><term>Fourier</term><term>Fourier series</term><term>Frequency domain</term><term>Gaussian probability density function</term><term>Inner race</term><term>Inner race fault</term><term>Lter</term><term>Ltering</term><term>Machine signals</term><term>Mechanical systems</term><term>More detail</term><term>Next section</term><term>Other hand</term><term>Other words</term><term>Outer race</term><term>Outer race fault</term><term>Point process</term><term>Previous paragraph</term><term>Randall</term><term>Recent years</term><term>Same parameters</term><term>Same result</term><term>Same time</term><term>Second order</term><term>Shaft speed</term><term>Shaft speeds</term><term>Signal processing</term><term>Spectral</term><term>Spectral band</term><term>Spectral correlation</term><term>Spectral correlation analysis</term><term>Spectral density</term><term>Squared</term><term>Squared envelope</term><term>Squared envelope analysis</term><term>Squared magnitude</term><term>Squared magnitude signal</term><term>Standard deviation</term><term>Stationary process</term><term>Statistical model</term><term>Statistical properties</term><term>Stochastic</term><term>Stochastic part</term><term>Stochastic process</term><term>System processing</term><term>Time signal</term><term>Useful information</term><term>Vibration</term><term>Vibration signal</term><term>Vibration signals</term></keywords></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Abstract: In recent years there has been an increasing interest in applying cyclostationary analysis to the diagnostics of machine vibration signals. This is because some machine signals, while being almost periodic, are not exactly phase-locked to shaft speeds, and thus even after compensation for speed fluctuation cannot be extracted by synchronous averaging. Typical examples are the combustion events in IC engines, which vary from cycle to cycle, and impulsive signals from faults in rolling element bearings, which are affected by minor but randomly varying slip. Two main tools for the analysis of cyclostationary signals are the two-dimensional autocorrelation function vs central time on the one axis and time displacement around the central time on the other, and its two-dimensional Fourier transform known as the spectral correlation. The latter can be quite complex to interpret, so some authors have suggested integrating it over all frequencies to obtain a Fourier series spectrumvs cyclic frequency. In this paper, it is shown that this gives the same result as a Fourier transform of the average squared envelope of the signal, which is much easier to obtain directly. Not only that, envelope analysis has long been used in the diagnostics of rolling element bearing signals, and some of the experience gained can be carried over to spectral correlation analysis. There is a possibility that the full spectral correlation may still give some advantage in distinguishing between modulation effects due to gear rotations and bearing inner race rotations (even at the same speed) by virtue of the different amounts of randomness associated with each.</div></front></TEI><double idat="0888-3270:2001:Randall R:the:relationship:between"><INIST><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en" level="a">The relationship between spectral correlation and envelope analysis in the diagnostics of bearing faults and other cyclostationary machine signals</title><author><name sortKey="Randall, R B" sort="Randall, R B" uniqKey="Randall R" first="R. B." last="Randall">R. B. Randall</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>School of Mechanical and Manufacturing Engineering, The University of New South Wales</s1><s2>Sydney 2052</s2><s3>AUS</s3><sZ>1 aut.</sZ></inist:fA14><country>Australie</country><placeName><settlement type="city">Sydney</settlement><region type="état">Nouvelle-Galles du Sud</region></placeName></affiliation></author><author><name sortKey="Antoni, J" sort="Antoni, J" uniqKey="Antoni J" first="J." last="Antoni">J. Antoni</name><affiliation wicri:level="1"><inist:fA14 i1="02"><s1>Laboratoire d'Analyse des Signaux et des Processus Industriels (LASPI), IUT de Roanne</s1><s2>42334 Roanne</s2><s3>FRA</s3><sZ>2 aut.</sZ></inist:fA14><country>France</country><wicri:noRegion>42334 Roanne</wicri:noRegion><wicri:noRegion>IUT de Roanne</wicri:noRegion><wicri:noRegion>42334 Roanne</wicri:noRegion></affiliation></author><author><name sortKey="Chobsaard, S" sort="Chobsaard, S" uniqKey="Chobsaard S" first="S." last="Chobsaard">S. Chobsaard</name><affiliation wicri:level="1"><inist:fA14 i1="03"><s1>Department of Engineering Development, Royal Thai Naval Dockyard</s1><s3>THA</s3><sZ>3 aut.</sZ></inist:fA14><country>Thaïlande</country><wicri:noRegion>Department of Engineering Development, Royal Thai Naval Dockyard</wicri:noRegion></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">INIST</idno><idno type="inist">02-0056686</idno><date when="2001">2001</date><idno type="stanalyst">PASCAL 02-0056686 INIST</idno><idno type="RBID">Pascal:02-0056686</idno><idno type="wicri:Area/PascalFrancis/Corpus">005A26</idno><idno type="wicri:Area/PascalFrancis/Curation">000713</idno><idno type="wicri:Area/PascalFrancis/Checkpoint">005649</idno><idno type="wicri:explorRef" wicri:stream="PascalFrancis" wicri:step="Checkpoint">005649</idno><idno type="wicri:doubleKey">0888-3270:2001:Randall R:the:relationship:between</idno><idno type="wicri:Area/Main/Merge">00C994</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">The relationship between spectral correlation and envelope analysis in the diagnostics of bearing faults and other cyclostationary machine signals</title><author><name sortKey="Randall, R B" sort="Randall, R B" uniqKey="Randall R" first="R. B." last="Randall">R. B. Randall</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>School of Mechanical and Manufacturing Engineering, The University of New South Wales</s1><s2>Sydney 2052</s2><s3>AUS</s3><sZ>1 aut.</sZ></inist:fA14><country>Australie</country><placeName><settlement type="city">Sydney</settlement><region type="état">Nouvelle-Galles du Sud</region></placeName></affiliation></author><author><name sortKey="Antoni, J" sort="Antoni, J" uniqKey="Antoni J" first="J." last="Antoni">J. Antoni</name><affiliation wicri:level="1"><inist:fA14 i1="02"><s1>Laboratoire d'Analyse des Signaux et des Processus Industriels (LASPI), IUT de Roanne</s1><s2>42334 Roanne</s2><s3>FRA</s3><sZ>2 aut.</sZ></inist:fA14><country>France</country><wicri:noRegion>42334 Roanne</wicri:noRegion><wicri:noRegion>IUT de Roanne</wicri:noRegion><wicri:noRegion>42334 Roanne</wicri:noRegion></affiliation></author><author><name sortKey="Chobsaard, S" sort="Chobsaard, S" uniqKey="Chobsaard S" first="S." last="Chobsaard">S. Chobsaard</name><affiliation wicri:level="1"><inist:fA14 i1="03"><s1>Department of Engineering Development, Royal Thai Naval Dockyard</s1><s3>THA</s3><sZ>3 aut.</sZ></inist:fA14><country>Thaïlande</country><wicri:noRegion>Department of Engineering Development, Royal Thai Naval Dockyard</wicri:noRegion></affiliation></author></analytic><series><title level="j" type="main">Mechanical systems and signal processing</title><title level="j" type="abbreviated">Mech. syst. signal process.</title><idno type="ISSN">0888-3270</idno><imprint><date when="2001">2001</date></imprint></series></biblStruct></sourceDesc><seriesStmt><title level="j" type="main">Mechanical systems and signal processing</title><title level="j" type="abbreviated">Mech. syst. signal process.</title><idno type="ISSN">0888-3270</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Cyclostationarity</term><term>Defect detection</term><term>Fault diagnostic</term><term>Fourier transformation</term><term>Gear</term><term>Measurement method</term><term>Monitoring</term><term>Non stationary process</term><term>Rolling bearing</term><term>Shaft</term><term>Signal envelope</term><term>Signal processing</term><term>Spectral analysis</term><term>Statistical analysis</term><term>Vibration</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Méthode mesure</term><term>Diagnostic panne</term><term>Détection défaut</term><term>Monitorage</term><term>Vibration</term><term>Arbre transmission</term><term>Engrenage</term><term>Palier roulement</term><term>Traitement signal</term><term>Processus non stationnaire</term><term>Analyse spectrale</term><term>Analyse statistique</term><term>Enveloppe signal</term><term>Transformation Fourier</term><term>4680</term><term>Cyclostationnarité</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">In recent years there has been an increasing interest in applying cyclostationary analysis to the diagnostics of machine vibration signals. This is because some machine signals, while being almost periodic, are not exactly phase-locked to shaft speeds, and thus even after compensation for speed fluctuation cannot be extracted by synchronous averaging. Typical examples are the combustion events in IC engines, which vary from cycle to cycle, and impulsive signals from faults in rolling element bearings, which are affected by minor but randomly varying slip. Two main tools for the analysis of cyclostationary signals are the two-dimensional autocorrelation function vs central time on the one axis and time displacement around the central time on the other, and its two-dimensional Fourier transform known as the spectral correlation. The latter can be quite complex to interpret, so some authors have suggested integrating it over all frequencies to obtain a Fourier series spectrum vs cyclic frequency. In this paper, it is shown that this gives the same result as a Fourier transform of the average squared envelope of the signal, which is much easier to obtain directly. Not only that, envelope analysis has long been used in the diagnostics of rolling element bearing signals, and some of the experience gained can be carried over to spectral correlation analysis. There is a possibility that the full spectral correlation may still give some advantage in distinguishing between modulation effects due to gear rotations and bearing inner race rotations (even at the same speed) by virtue of the different amounts of randomness associated with each.</div></front></TEI></INIST><ISTEX><TEI wicri:istexFullTextTei="biblStruct"><teiHeader><fileDesc><titleStmt><title xml:lang="en">THE RELATIONSHIP BETWEEN SPECTRAL CORRELATION AND ENVELOPE ANALYSIS IN THE DIAGNOSTICS OF BEARING FAULTS AND OTHER CYCLOSTATIONARY MACHINE SIGNALS</title><author><name sortKey="Randall, R B" sort="Randall, R B" uniqKey="Randall R" first="R. B." last="Randall">R. B. Randall</name></author><author><name sortKey="Antoni, J" sort="Antoni, J" uniqKey="Antoni J" first="J." last="Antoni">J. Antoni</name></author><author><name sortKey="Chobsaard, S" sort="Chobsaard, S" uniqKey="Chobsaard S" first="S." last="Chobsaard">S. Chobsaard</name></author></titleStmt><publicationStmt><idno type="wicri:source">ISTEX</idno><idno type="RBID">ISTEX:027C3B100069021CBCA7E9B8B13DE3F9CCCAB141</idno><date when="2001" year="2001">2001</date><idno type="doi">10.1006/mssp.2001.1415</idno><idno type="url">https://api.istex.fr/document/027C3B100069021CBCA7E9B8B13DE3F9CCCAB141/fulltext/pdf</idno><idno type="wicri:Area/Istex/Corpus">000048</idno><idno type="wicri:explorRef" wicri:stream="Istex" wicri:step="Corpus" wicri:corpus="ISTEX">000048</idno><idno type="wicri:Area/Istex/Curation">000048</idno><idno type="wicri:Area/Istex/Checkpoint">001D58</idno><idno type="wicri:explorRef" wicri:stream="Istex" wicri:step="Checkpoint">001D58</idno><idno type="wicri:doubleKey">0888-3270:2001:Randall R:the:relationship:between</idno><idno type="wicri:Area/Main/Merge">00C799</idno></publicationStmt><sourceDesc><biblStruct><analytic><title level="a" type="main" xml:lang="en">THE RELATIONSHIP BETWEEN SPECTRAL CORRELATION AND ENVELOPE ANALYSIS IN THE DIAGNOSTICS OF BEARING FAULTS AND OTHER CYCLOSTATIONARY MACHINE SIGNALS</title><author><name sortKey="Randall, R B" sort="Randall, R B" uniqKey="Randall R" first="R. B." last="Randall">R. B. Randall</name><affiliation wicri:level="1"><country xml:lang="fr">Australie</country><wicri:regionArea>School of Mechanical and Manufacturing Engineering, The University of New South Wales, Sydney, 2052</wicri:regionArea><wicri:noRegion>2052</wicri:noRegion></affiliation></author><author><name sortKey="Antoni, J" sort="Antoni, J" uniqKey="Antoni J" first="J." last="Antoni">J. Antoni</name><affiliation wicri:level="3"><country xml:lang="fr">France</country><wicri:regionArea>Laboratoire d'Analyse des Signaux et des Processus Industriels (LASPI), IUT de Roanne, 42334, Roanne</wicri:regionArea><placeName><region type="region" nuts="2">Auvergne-Rhône-Alpes</region><region type="old region" nuts="2">Rhône-Alpes</region><settlement type="city">Roanne</settlement></placeName></affiliation></author><author><name sortKey="Chobsaard, S" sort="Chobsaard, S" uniqKey="Chobsaard S" first="S." last="Chobsaard">S. Chobsaard</name><affiliation wicri:level="1"><country xml:lang="fr">Thaïlande</country><wicri:regionArea>Department of Engineering Development, Royal Thai Naval Dockyard</wicri:regionArea><wicri:noRegion>Royal Thai Naval Dockyard</wicri:noRegion></affiliation></author></analytic><monogr></monogr><series><title level="j">Mechanical Systems and Signal Processing</title><title level="j" type="abbrev">YMSSP</title><idno type="ISSN">0888-3270</idno><imprint><publisher>ELSEVIER</publisher><date type="published" when="2001">2001</date><biblScope unit="volume">15</biblScope><biblScope unit="issue">5</biblScope><biblScope unit="page" from="945">945</biblScope><biblScope unit="page" to="962">962</biblScope></imprint><idno type="ISSN">0888-3270</idno></series></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0888-3270</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Academic press</term><term>Additive background noise</term><term>Aforementioned solutions</term><term>Aliasing</term><term>Amplitude modulation</term><term>Analytic signal</term><term>Autocovariance function</term><term>Central time</term><term>Classical envelope analysis</term><term>Cyclic</term><term>Cyclic frequencies</term><term>Cyclic frequency</term><term>Cyclostationary</term><term>Cyclostationary signals</term><term>Defect</term><term>Demodulated signal</term><term>Density function</term><term>Deterministic part</term><term>Digitised signal</term><term>Discrete spectrum</term><term>Element bearings</term><term>Envelope analysis</term><term>Fault signals</term><term>Figure displays</term><term>Fourier</term><term>Fourier series</term><term>Frequency domain</term><term>Gaussian probability density function</term><term>Inner race</term><term>Inner race fault</term><term>Lter</term><term>Ltering</term><term>Machine signals</term><term>Mechanical systems</term><term>More detail</term><term>Next section</term><term>Other hand</term><term>Other words</term><term>Outer race</term><term>Outer race fault</term><term>Point process</term><term>Previous paragraph</term><term>Randall</term><term>Recent years</term><term>Same parameters</term><term>Same result</term><term>Same time</term><term>Second order</term><term>Shaft speed</term><term>Shaft speeds</term><term>Signal processing</term><term>Spectral</term><term>Spectral band</term><term>Spectral correlation</term><term>Spectral correlation analysis</term><term>Spectral density</term><term>Squared</term><term>Squared envelope</term><term>Squared envelope analysis</term><term>Squared magnitude</term><term>Squared magnitude signal</term><term>Standard deviation</term><term>Stationary process</term><term>Statistical model</term><term>Statistical properties</term><term>Stochastic</term><term>Stochastic part</term><term>Stochastic process</term><term>System processing</term><term>Time signal</term><term>Useful information</term><term>Vibration</term><term>Vibration signal</term><term>Vibration signals</term></keywords><keywords scheme="Teeft" xml:lang="en"><term>Academic press</term><term>Additive background noise</term><term>Aforementioned solutions</term><term>Aliasing</term><term>Amplitude modulation</term><term>Analytic signal</term><term>Autocovariance function</term><term>Central time</term><term>Classical envelope analysis</term><term>Cyclic</term><term>Cyclic frequencies</term><term>Cyclic frequency</term><term>Cyclostationary</term><term>Cyclostationary signals</term><term>Defect</term><term>Demodulated signal</term><term>Density function</term><term>Deterministic part</term><term>Digitised signal</term><term>Discrete spectrum</term><term>Element bearings</term><term>Envelope analysis</term><term>Fault signals</term><term>Figure displays</term><term>Fourier</term><term>Fourier series</term><term>Frequency domain</term><term>Gaussian probability density function</term><term>Inner race</term><term>Inner race fault</term><term>Lter</term><term>Ltering</term><term>Machine signals</term><term>Mechanical systems</term><term>More detail</term><term>Next section</term><term>Other hand</term><term>Other words</term><term>Outer race</term><term>Outer race fault</term><term>Point process</term><term>Previous paragraph</term><term>Randall</term><term>Recent years</term><term>Same parameters</term><term>Same result</term><term>Same time</term><term>Second order</term><term>Shaft speed</term><term>Shaft speeds</term><term>Signal processing</term><term>Spectral</term><term>Spectral band</term><term>Spectral correlation</term><term>Spectral correlation analysis</term><term>Spectral density</term><term>Squared</term><term>Squared envelope</term><term>Squared envelope analysis</term><term>Squared magnitude</term><term>Squared magnitude signal</term><term>Standard deviation</term><term>Stationary process</term><term>Statistical model</term><term>Statistical properties</term><term>Stochastic</term><term>Stochastic part</term><term>Stochastic process</term><term>System processing</term><term>Time signal</term><term>Useful information</term><term>Vibration</term><term>Vibration signal</term><term>Vibration signals</term></keywords></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Abstract: In recent years there has been an increasing interest in applying cyclostationary analysis to the diagnostics of machine vibration signals. This is because some machine signals, while being almost periodic, are not exactly phase-locked to shaft speeds, and thus even after compensation for speed fluctuation cannot be extracted by synchronous averaging. Typical examples are the combustion events in IC engines, which vary from cycle to cycle, and impulsive signals from faults in rolling element bearings, which are affected by minor but randomly varying slip. Two main tools for the analysis of cyclostationary signals are the two-dimensional autocorrelation function vs central time on the one axis and time displacement around the central time on the other, and its two-dimensional Fourier transform known as the spectral correlation. The latter can be quite complex to interpret, so some authors have suggested integrating it over all frequencies to obtain a Fourier series spectrumvs cyclic frequency. In this paper, it is shown that this gives the same result as a Fourier transform of the average squared envelope of the signal, which is much easier to obtain directly. Not only that, envelope analysis has long been used in the diagnostics of rolling element bearing signals, and some of the experience gained can be carried over to spectral correlation analysis. There is a possibility that the full spectral correlation may still give some advantage in distinguishing between modulation effects due to gear rotations and bearing inner race rotations (even at the same speed) by virtue of the different amounts of randomness associated with each.</div></front></TEI></ISTEX></double></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Wicri/Asie/explor/AustralieFrV1/Data/Main/Curation
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 00B954 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Curation/biblio.hfd -nk 00B954 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Wicri/Asie
|area= AustralieFrV1
|flux= Main
|étape= Curation
|type= RBID
|clé= ISTEX:027C3B100069021CBCA7E9B8B13DE3F9CCCAB141
|texte= THE RELATIONSHIP BETWEEN SPECTRAL CORRELATION AND ENVELOPE ANALYSIS IN THE DIAGNOSTICS OF BEARING FAULTS AND OTHER CYCLOSTATIONARY MACHINE SIGNALS
}}
| This area was generated with Dilib version V0.6.33. |  |