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Joint High-Order Synchrosqueezing Transform and Multi-Taper Empirical Wavelet Transform for Fault Diagnosis of Wind Turbine Planetary Gearbox under Nonstationary Conditions
Wind turbines usually operate under nonstationary conditions, such as wide-range speed fluctuation and time-varying load. Its critical component, the planetary gearbox, is prone to malfunction or failure, which leads to downtime and repair costs. Therefore, fault diagnosis and condition monitoring f...
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Published in: | Sensors (Basel, Switzerland) Switzerland), 2018-01, Vol.18 (1), p.150 |
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description | Wind turbines usually operate under nonstationary conditions, such as wide-range speed fluctuation and time-varying load. Its critical component, the planetary gearbox, is prone to malfunction or failure, which leads to downtime and repair costs. Therefore, fault diagnosis and condition monitoring for the planetary gearbox in wind turbines is a vital research topic. Meanwhile, the signals measured by the vibration sensors mounted in the gearbox exhibit time-varying and nonstationary features. In this study, a novel time-frequency method based on high-order synchrosqueezing transform (SST) and multi-taper empirical wavelet transform (MTEWT) is proposed for the wind turbine planetary gearbox under nonstationary conditions. The high-order SST uses accurate instantaneous frequency approximations to obtain a sharper time-frequency representation (TFR). As the acquired signal consists of many components, like the meshing and rotating components of the gear and bearing, the fault component may be masked by other unrelated components. The MTEWT is used to separate the fault feature from the masking components. A variety of experimental signals of the wind turbine planetary gearbox under nonstationary conditions have been analyzed to demonstrate the effectiveness and robustness of the proposed method. Results show that the proposed method is effective in diagnosing both gear and bearing faults. |
doi_str_mv | 10.3390/s18010150 |
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Its critical component, the planetary gearbox, is prone to malfunction or failure, which leads to downtime and repair costs. Therefore, fault diagnosis and condition monitoring for the planetary gearbox in wind turbines is a vital research topic. Meanwhile, the signals measured by the vibration sensors mounted in the gearbox exhibit time-varying and nonstationary features. In this study, a novel time-frequency method based on high-order synchrosqueezing transform (SST) and multi-taper empirical wavelet transform (MTEWT) is proposed for the wind turbine planetary gearbox under nonstationary conditions. The high-order SST uses accurate instantaneous frequency approximations to obtain a sharper time-frequency representation (TFR). As the acquired signal consists of many components, like the meshing and rotating components of the gear and bearing, the fault component may be masked by other unrelated components. The MTEWT is used to separate the fault feature from the masking components. A variety of experimental signals of the wind turbine planetary gearbox under nonstationary conditions have been analyzed to demonstrate the effectiveness and robustness of the proposed method. Results show that the proposed method is effective in diagnosing both gear and bearing faults.</description><identifier>ISSN: 1424-8220</identifier><identifier>EISSN: 1424-8220</identifier><identifier>DOI: 10.3390/s18010150</identifier><identifier>PMID: 29316668</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Critical components ; Downtime ; empirical wavelet transform ; Fault diagnosis ; Gear trains ; Masking ; Meshing ; multi-taper ; synchrosqueezing transform ; time-frequency analysis ; Variation ; Vibration measurement ; Wavelet transforms ; wind turbine gearbox</subject><ispartof>Sensors (Basel, Switzerland), 2018-01, Vol.18 (1), p.150</ispartof><rights>2018. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). 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Its critical component, the planetary gearbox, is prone to malfunction or failure, which leads to downtime and repair costs. Therefore, fault diagnosis and condition monitoring for the planetary gearbox in wind turbines is a vital research topic. Meanwhile, the signals measured by the vibration sensors mounted in the gearbox exhibit time-varying and nonstationary features. In this study, a novel time-frequency method based on high-order synchrosqueezing transform (SST) and multi-taper empirical wavelet transform (MTEWT) is proposed for the wind turbine planetary gearbox under nonstationary conditions. The high-order SST uses accurate instantaneous frequency approximations to obtain a sharper time-frequency representation (TFR). As the acquired signal consists of many components, like the meshing and rotating components of the gear and bearing, the fault component may be masked by other unrelated components. The MTEWT is used to separate the fault feature from the masking components. A variety of experimental signals of the wind turbine planetary gearbox under nonstationary conditions have been analyzed to demonstrate the effectiveness and robustness of the proposed method. Results show that the proposed method is effective in diagnosing both gear and bearing faults.</description><subject>Critical components</subject><subject>Downtime</subject><subject>empirical wavelet transform</subject><subject>Fault diagnosis</subject><subject>Gear trains</subject><subject>Masking</subject><subject>Meshing</subject><subject>multi-taper</subject><subject>synchrosqueezing transform</subject><subject>time-frequency analysis</subject><subject>Variation</subject><subject>Vibration measurement</subject><subject>Wavelet transforms</subject><subject>wind turbine gearbox</subject><issn>1424-8220</issn><issn>1424-8220</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpdkttu1DAQhiMEoge44AWQJW7gIuBDYsc3SNXSEyoUiUW9tJxkkvUqsRfbqVqeiYfEYctqi2SN7fGnX79nJsteEfyeMYk_BFJhgkmJn2SHpKBFXlGKn-6dD7KjENYYU8ZY9Tw7oJIRznl1mP3-7IyN6ML0q_zat-DR93vbrLwLPyeAX8b2aOm1DZ3zI9K2RV-mIZp8qTcJPR03xptGD-hG38IAcY9NAZ3pBKNPRvfWBROQ69CNSRrLydfGAvo2aAtR-3t0DtrX7g5Ndrbw1dkQdTTOzm8LZ1szX8KL7FmnhwAvH_bj7MfZ6XJxkV9dn18uTq7ypuAy5iBFq4tacKgLXNB5YQmyAgDdlXVZUFl0nAGhElKUWgggnaQJJ6QuSnacXW51W6fXauPNmHwop436m3C-V9pH0wyg2koTSYQUtG0KELSuU5VLTqqOQ9uUIml93GptpnpMKbDR6-GR6OMXa1aqd7eqFLIUJUkCbx8EvEs9CVGNJjQwzLVzU1BEVrLkFRc4oW_-Q9du8jaVSqUS0IoQxuffvdtSTepy8NDtzBCs5nlSu3lK7Ot99zvy3wCxP3NPyLs</recordid><startdate>20180107</startdate><enddate>20180107</enddate><creator>Hu, Yue</creator><creator>Tu, Xiaotong</creator><creator>Li, Fucai</creator><creator>Meng, Guang</creator><general>MDPI AG</general><general>MDPI</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-5365-2593</orcidid><orcidid>https://orcid.org/0000-0002-7190-2429</orcidid></search><sort><creationdate>20180107</creationdate><title>Joint High-Order Synchrosqueezing Transform and Multi-Taper Empirical Wavelet Transform for Fault Diagnosis of Wind Turbine Planetary Gearbox under Nonstationary Conditions</title><author>Hu, Yue ; Tu, Xiaotong ; Li, Fucai ; Meng, Guang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c469t-e97da4b76eb4042042009e98eeeaf5b54294f63e129e3e19a77e1f92eb411b453</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Critical components</topic><topic>Downtime</topic><topic>empirical wavelet transform</topic><topic>Fault diagnosis</topic><topic>Gear trains</topic><topic>Masking</topic><topic>Meshing</topic><topic>multi-taper</topic><topic>synchrosqueezing transform</topic><topic>time-frequency analysis</topic><topic>Variation</topic><topic>Vibration measurement</topic><topic>Wavelet transforms</topic><topic>wind turbine gearbox</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hu, Yue</creatorcontrib><creatorcontrib>Tu, Xiaotong</creatorcontrib><creatorcontrib>Li, Fucai</creatorcontrib><creatorcontrib>Meng, Guang</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Publicly Available Content (ProQuest)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Sensors (Basel, Switzerland)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hu, Yue</au><au>Tu, Xiaotong</au><au>Li, Fucai</au><au>Meng, Guang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Joint High-Order Synchrosqueezing Transform and Multi-Taper Empirical Wavelet Transform for Fault Diagnosis of Wind Turbine Planetary Gearbox under Nonstationary Conditions</atitle><jtitle>Sensors (Basel, Switzerland)</jtitle><addtitle>Sensors (Basel)</addtitle><date>2018-01-07</date><risdate>2018</risdate><volume>18</volume><issue>1</issue><spage>150</spage><pages>150-</pages><issn>1424-8220</issn><eissn>1424-8220</eissn><abstract>Wind turbines usually operate under nonstationary conditions, such as wide-range speed fluctuation and time-varying load. Its critical component, the planetary gearbox, is prone to malfunction or failure, which leads to downtime and repair costs. Therefore, fault diagnosis and condition monitoring for the planetary gearbox in wind turbines is a vital research topic. Meanwhile, the signals measured by the vibration sensors mounted in the gearbox exhibit time-varying and nonstationary features. In this study, a novel time-frequency method based on high-order synchrosqueezing transform (SST) and multi-taper empirical wavelet transform (MTEWT) is proposed for the wind turbine planetary gearbox under nonstationary conditions. The high-order SST uses accurate instantaneous frequency approximations to obtain a sharper time-frequency representation (TFR). As the acquired signal consists of many components, like the meshing and rotating components of the gear and bearing, the fault component may be masked by other unrelated components. The MTEWT is used to separate the fault feature from the masking components. 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subjects | Critical components Downtime empirical wavelet transform Fault diagnosis Gear trains Masking Meshing multi-taper synchrosqueezing transform time-frequency analysis Variation Vibration measurement Wavelet transforms wind turbine gearbox |
title | Joint High-Order Synchrosqueezing Transform and Multi-Taper Empirical Wavelet Transform for Fault Diagnosis of Wind Turbine Planetary Gearbox under Nonstationary Conditions |
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