Correlation analysis of noise sound pressure and vibration in aluminum alloy milling
To study the correlation between noise and vibration during dry milling of aluminum alloy, a synchronous acquisition system of noise and vibration was established. Based on the experimental data, the effects of three milling parameters on milling noise and milling vibration were analyzed. Based on t...
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| Veröffentlicht in: | Journal of vibration and control 2022-02, Vol.28 (3-4), p.276-289 |
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| container_title | Journal of vibration and control |
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| creator | Hu, Yuting Li, Shuncai Deng, Xing Vadim, Slatin |
| description | To study the correlation between noise and vibration during dry milling of aluminum alloy, a synchronous acquisition system of noise and vibration was established. Based on the experimental data, the effects of three milling parameters on milling noise and milling vibration were analyzed. Based on the least square method and MATLAB software programming, the multiple regression models of milling noise on milling parameters and milling vibration were established. According to the regression models, it is found that there is a strong correlation between milling noise, milling parameters, and milling vibration. The maximum value of the correlation coefficient R is 0.98. It also shows that the regression models based on milling parameters and milling vibration can well predict the noise of aluminum alloy during milling. In addition, the obtained model can provide a control equation for the future coupling analysis of vibration and noise and for the numerical simulation. |
| doi_str_mv | 10.1177/1077546320975977 |
| format | Article |
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Based on the experimental data, the effects of three milling parameters on milling noise and milling vibration were analyzed. Based on the least square method and MATLAB software programming, the multiple regression models of milling noise on milling parameters and milling vibration were established. According to the regression models, it is found that there is a strong correlation between milling noise, milling parameters, and milling vibration. The maximum value of the correlation coefficient R is 0.98. It also shows that the regression models based on milling parameters and milling vibration can well predict the noise of aluminum alloy during milling. In addition, the obtained model can provide a control equation for the future coupling analysis of vibration and noise and for the numerical simulation.</description><identifier>ISSN: 1077-5463</identifier><identifier>EISSN: 1741-2986</identifier><identifier>DOI: 10.1177/1077546320975977</identifier><language>eng</language><publisher>London, England: SAGE Publications</publisher><subject>Aluminum ; Aluminum alloys ; Aluminum base alloys ; Correlation analysis ; Correlation coefficient ; Correlation coefficients ; Multiple regression models ; Noise ; Noise prediction ; Parameters ; Sound pressure ; Vibration ; Vibration analysis</subject><ispartof>Journal of vibration and control, 2022-02, Vol.28 (3-4), p.276-289</ispartof><rights>The Author(s) 2020</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c309t-fa2063282a3016f7150ca2607d8277e0a540a1903615e21e3587ad7eef4159c73</citedby><cites>FETCH-LOGICAL-c309t-fa2063282a3016f7150ca2607d8277e0a540a1903615e21e3587ad7eef4159c73</cites><orcidid>0000-0002-3284-8001 ; 0000-0003-1635-3452</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.sagepub.com/doi/pdf/10.1177/1077546320975977$$EPDF$$P50$$Gsage$$H</linktopdf><linktohtml>$$Uhttps://journals.sagepub.com/doi/10.1177/1077546320975977$$EHTML$$P50$$Gsage$$H</linktohtml><link.rule.ids>314,780,784,21819,27924,27925,43621,43622</link.rule.ids></links><search><creatorcontrib>Hu, Yuting</creatorcontrib><creatorcontrib>Li, Shuncai</creatorcontrib><creatorcontrib>Deng, Xing</creatorcontrib><creatorcontrib>Vadim, Slatin</creatorcontrib><title>Correlation analysis of noise sound pressure and vibration in aluminum alloy milling</title><title>Journal of vibration and control</title><description>To study the correlation between noise and vibration during dry milling of aluminum alloy, a synchronous acquisition system of noise and vibration was established. Based on the experimental data, the effects of three milling parameters on milling noise and milling vibration were analyzed. Based on the least square method and MATLAB software programming, the multiple regression models of milling noise on milling parameters and milling vibration were established. According to the regression models, it is found that there is a strong correlation between milling noise, milling parameters, and milling vibration. The maximum value of the correlation coefficient R is 0.98. It also shows that the regression models based on milling parameters and milling vibration can well predict the noise of aluminum alloy during milling. In addition, the obtained model can provide a control equation for the future coupling analysis of vibration and noise and for the numerical simulation.</description><subject>Aluminum</subject><subject>Aluminum alloys</subject><subject>Aluminum base alloys</subject><subject>Correlation analysis</subject><subject>Correlation coefficient</subject><subject>Correlation coefficients</subject><subject>Multiple regression models</subject><subject>Noise</subject><subject>Noise prediction</subject><subject>Parameters</subject><subject>Sound pressure</subject><subject>Vibration</subject><subject>Vibration analysis</subject><issn>1077-5463</issn><issn>1741-2986</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp1kM1LxDAQxYMouK7ePRY8VydJk2mOsvgFC17Wc4ltumRJmzWzFfa_N1JBEDzNg_d7j5lh7JrDLeeIdxwQVaWlAIPKIJ6wBceKl8LU-jTrbJff_jm7INoBQFVxWLDNKqbkgj34OBZ2tOFInorYF2P05AqK09gV--SIpuQy0BWf_j3NuM-JMA1-nIYsQjwWgw_Bj9tLdtbbQO7qZy7Z2-PDZvVcrl-fXlb367KVYA5lbwXkhWthJXDdI1fQWqEBu1ogOrCqAssNSM2VE9xJVaPt0Lm-4sq0KJfsZu7dp_gxOTo0uzilfAQ1QguBWio0mYKZalMkSq5v9skPNh0bDs3375q_v8uRco6Q3brf0n_5L6q3bZs</recordid><startdate>202202</startdate><enddate>202202</enddate><creator>Hu, Yuting</creator><creator>Li, Shuncai</creator><creator>Deng, Xing</creator><creator>Vadim, Slatin</creator><general>SAGE Publications</general><general>SAGE PUBLICATIONS, INC</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-3284-8001</orcidid><orcidid>https://orcid.org/0000-0003-1635-3452</orcidid></search><sort><creationdate>202202</creationdate><title>Correlation analysis of noise sound pressure and vibration in aluminum alloy milling</title><author>Hu, Yuting ; Li, Shuncai ; Deng, Xing ; Vadim, Slatin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c309t-fa2063282a3016f7150ca2607d8277e0a540a1903615e21e3587ad7eef4159c73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Aluminum</topic><topic>Aluminum alloys</topic><topic>Aluminum base alloys</topic><topic>Correlation analysis</topic><topic>Correlation coefficient</topic><topic>Correlation coefficients</topic><topic>Multiple regression models</topic><topic>Noise</topic><topic>Noise prediction</topic><topic>Parameters</topic><topic>Sound pressure</topic><topic>Vibration</topic><topic>Vibration analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hu, Yuting</creatorcontrib><creatorcontrib>Li, Shuncai</creatorcontrib><creatorcontrib>Deng, Xing</creatorcontrib><creatorcontrib>Vadim, Slatin</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</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 vibration and control</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hu, Yuting</au><au>Li, Shuncai</au><au>Deng, Xing</au><au>Vadim, Slatin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Correlation analysis of noise sound pressure and vibration in aluminum alloy milling</atitle><jtitle>Journal of vibration and control</jtitle><date>2022-02</date><risdate>2022</risdate><volume>28</volume><issue>3-4</issue><spage>276</spage><epage>289</epage><pages>276-289</pages><issn>1077-5463</issn><eissn>1741-2986</eissn><abstract>To study the correlation between noise and vibration during dry milling of aluminum alloy, a synchronous acquisition system of noise and vibration was established. Based on the experimental data, the effects of three milling parameters on milling noise and milling vibration were analyzed. Based on the least square method and MATLAB software programming, the multiple regression models of milling noise on milling parameters and milling vibration were established. According to the regression models, it is found that there is a strong correlation between milling noise, milling parameters, and milling vibration. The maximum value of the correlation coefficient R is 0.98. It also shows that the regression models based on milling parameters and milling vibration can well predict the noise of aluminum alloy during milling. 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| subjects | Aluminum Aluminum alloys Aluminum base alloys Correlation analysis Correlation coefficient Correlation coefficients Multiple regression models Noise Noise prediction Parameters Sound pressure Vibration Vibration analysis |
| title | Correlation analysis of noise sound pressure and vibration in aluminum alloy milling |
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