Fault analysis on continuous variable transmission using DB-06 wavelet decomposition and fault classification using ANN
This study aims at developing a novel method for condition monitoring technique for detection and classification of developing faults and increase the working life of continuous variable transmission (CVT) using Daubechies Wavelet 06 (DB-06). The vibration data is collected for 4 different types of...
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| Veröffentlicht in: | Journal of intelligent & fuzzy systems 2021-01, Vol.41 (1), p.1297-1307 |
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| container_title | Journal of intelligent & fuzzy systems |
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| creator | Narendiranath Babu, T. Senthilnathan, N. Pancholi, Shailesh Nikhil Kumar, S.P. Rama Prabha, D. Mohammed, Noor Wahab, Razia Sultana |
| description | This study aims at developing a novel method for condition monitoring technique for detection and classification of developing faults and increase the working life of continuous variable transmission (CVT) using Daubechies Wavelet 06 (DB-06). The vibration data is collected for 4 different types of faults and healthy condition. Using a magnetic accelerometer and signal analyser, vibration data is collected from the system in the time-domain which is then used as input for a MATLAB code producing the plot of the frequency-domain signal. Maximum frequency is determined to diagnose the faults which are induced over three different belts. Collected data for large scale automotive system (CVT) is used to train the network and then it is tested based on random data points. Faults were classified using ANN with a classification rate of 90.8 %. |
| doi_str_mv | 10.3233/JIFS-210199 |
| format | Article |
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The vibration data is collected for 4 different types of faults and healthy condition. Using a magnetic accelerometer and signal analyser, vibration data is collected from the system in the time-domain which is then used as input for a MATLAB code producing the plot of the frequency-domain signal. Maximum frequency is determined to diagnose the faults which are induced over three different belts. Collected data for large scale automotive system (CVT) is used to train the network and then it is tested based on random data points. 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Faults were classified using ANN with a classification rate of 90.8 %.</description><subject>Accelerometers</subject><subject>Classification</subject><subject>Condition monitoring</subject><subject>Continuity (mathematics)</subject><subject>Data collection</subject><subject>Data points</subject><subject>Fault detection</subject><subject>Fault diagnosis</subject><subject>Signal analyzers</subject><subject>Vibration</subject><issn>1064-1246</issn><issn>1875-8967</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNpFkD1PwzAURS0EEqUw8QcsMaKAPxrHHkshUFSVAZgjx7GRqzQufk6r_ntSisT07nDukd5F6JqSO844v3-dl-8Zo4QqdYJGVBZ5JpUoTodMxCSjbCLO0QXAihBa5IyM0K7UfZuw7nS7Bw84dNiELvmuDz3grY5e163FKeoO1h7AD0APvvvCjw8ZEXint7a1CTfWhPUmgE8HQncNdr9i0-qh5LzR6b86XS4v0ZnTLdirvztGn-XTx-wlW7w9z2fTRWaYoCmzVjdC5E4wKxgRkkuVC-KIFZxrQ5q8lkYKlVNquaKOFbmlrGG65tTVRio-RjdH7yaG795Cqlahj8O3ULHBpBgXEzlQt0fKxAAQras20a913FeUVIdlq8Oy1XFZ_gPP62ye</recordid><startdate>20210101</startdate><enddate>20210101</enddate><creator>Narendiranath Babu, T.</creator><creator>Senthilnathan, N.</creator><creator>Pancholi, Shailesh</creator><creator>Nikhil Kumar, S.P.</creator><creator>Rama Prabha, D.</creator><creator>Mohammed, Noor</creator><creator>Wahab, Razia Sultana</creator><general>IOS Press BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20210101</creationdate><title>Fault analysis on continuous variable transmission using DB-06 wavelet decomposition and fault classification using ANN</title><author>Narendiranath Babu, T. ; Senthilnathan, N. ; Pancholi, Shailesh ; Nikhil Kumar, S.P. ; Rama Prabha, D. ; Mohammed, Noor ; Wahab, Razia Sultana</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c261t-eead665f62e62068389560f0e633ac0d5b8c869511e391f275e12d2ab31fbc893</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Accelerometers</topic><topic>Classification</topic><topic>Condition monitoring</topic><topic>Continuity (mathematics)</topic><topic>Data collection</topic><topic>Data points</topic><topic>Fault detection</topic><topic>Fault diagnosis</topic><topic>Signal analyzers</topic><topic>Vibration</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Narendiranath Babu, T.</creatorcontrib><creatorcontrib>Senthilnathan, N.</creatorcontrib><creatorcontrib>Pancholi, Shailesh</creatorcontrib><creatorcontrib>Nikhil Kumar, S.P.</creatorcontrib><creatorcontrib>Rama Prabha, D.</creatorcontrib><creatorcontrib>Mohammed, Noor</creatorcontrib><creatorcontrib>Wahab, Razia Sultana</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Journal of intelligent & fuzzy systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Narendiranath Babu, T.</au><au>Senthilnathan, N.</au><au>Pancholi, Shailesh</au><au>Nikhil Kumar, S.P.</au><au>Rama Prabha, D.</au><au>Mohammed, Noor</au><au>Wahab, Razia Sultana</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Fault analysis on continuous variable transmission using DB-06 wavelet decomposition and fault classification using ANN</atitle><jtitle>Journal of intelligent & fuzzy systems</jtitle><date>2021-01-01</date><risdate>2021</risdate><volume>41</volume><issue>1</issue><spage>1297</spage><epage>1307</epage><pages>1297-1307</pages><issn>1064-1246</issn><eissn>1875-8967</eissn><abstract>This study aims at developing a novel method for condition monitoring technique for detection and classification of developing faults and increase the working life of continuous variable transmission (CVT) using Daubechies Wavelet 06 (DB-06). 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| source | Business Source Complete (EBSCO) |
| subjects | Accelerometers Classification Condition monitoring Continuity (mathematics) Data collection Data points Fault detection Fault diagnosis Signal analyzers Vibration |
| title | Fault analysis on continuous variable transmission using DB-06 wavelet decomposition and fault classification using ANN |
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