Garbage Crusher Fault Diagnosis Based on RBF Neural Network
The garbage crusher is a new kind of crusher for garbage crushing when processing Municipal Solid Waste (MSW). With the development of automatic equipment and the complication of structure and properties of the garbage crusher, the fault diagnosis of garbage crusher is very important. In this paper,...
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Veröffentlicht in: | Applied Mechanics and Materials 2009-10, Vol.16-19, p.971-975 |
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description | The garbage crusher is a new kind of crusher for garbage crushing when processing Municipal Solid Waste (MSW). With the development of automatic equipment and the complication of structure and properties of the garbage crusher, the fault diagnosis of garbage crusher is very important. In this paper, according to the fault symptoms and parameters, Radial Basis Function Neural Network (RBF NN) is used for fault diagnosis of the garbage crusher. The structure and inference of RBF NN are discussed in detail. The garbage crusher fault diagnosis model is established based on RBF network. At last, the fault of mechanical system is taken as an example of garbage crusher fault diagnosis. Training simulation results of the neural network are given base on MATLAB software. The result shows the RBF NN is suitable for fault diagnosis of garbage crusher. |
doi_str_mv | 10.4028/www.scientific.net/AMM.16-19.971 |
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With the development of automatic equipment and the complication of structure and properties of the garbage crusher, the fault diagnosis of garbage crusher is very important. In this paper, according to the fault symptoms and parameters, Radial Basis Function Neural Network (RBF NN) is used for fault diagnosis of the garbage crusher. The structure and inference of RBF NN are discussed in detail. The garbage crusher fault diagnosis model is established based on RBF network. At last, the fault of mechanical system is taken as an example of garbage crusher fault diagnosis. Training simulation results of the neural network are given base on MATLAB software. The result shows the RBF NN is suitable for fault diagnosis of garbage crusher.</description><identifier>ISSN: 1660-9336</identifier><identifier>ISSN: 1662-7482</identifier><identifier>ISBN: 9780878492992</identifier><identifier>ISBN: 0878492992</identifier><identifier>EISSN: 1662-7482</identifier><identifier>DOI: 10.4028/www.scientific.net/AMM.16-19.971</identifier><language>eng</language><publisher>Zurich: Trans Tech Publications Ltd</publisher><ispartof>Applied Mechanics and Materials, 2009-10, Vol.16-19, p.971-975</ispartof><rights>2009 Trans Tech Publications Ltd</rights><rights>Copyright Trans Tech Publications Ltd. Oct 2009</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c362t-484520a2e0b23f2dcfb7dab2ad7a3f130b1fac7008b84abb524762834f9664e03</citedby><cites>FETCH-LOGICAL-c362t-484520a2e0b23f2dcfb7dab2ad7a3f130b1fac7008b84abb524762834f9664e03</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttps://www.scientific.net/Image/TitleCover/875?width=600</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Li, Cong</creatorcontrib><creatorcontrib>Jing, Hui</creatorcontrib><creatorcontrib>Sun, Yong Hou</creatorcontrib><creatorcontrib>Huang, Mei Fa</creatorcontrib><title>Garbage Crusher Fault Diagnosis Based on RBF Neural Network</title><title>Applied Mechanics and Materials</title><description>The garbage crusher is a new kind of crusher for garbage crushing when processing Municipal Solid Waste (MSW). With the development of automatic equipment and the complication of structure and properties of the garbage crusher, the fault diagnosis of garbage crusher is very important. In this paper, according to the fault symptoms and parameters, Radial Basis Function Neural Network (RBF NN) is used for fault diagnosis of the garbage crusher. The structure and inference of RBF NN are discussed in detail. The garbage crusher fault diagnosis model is established based on RBF network. At last, the fault of mechanical system is taken as an example of garbage crusher fault diagnosis. Training simulation results of the neural network are given base on MATLAB software. 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With the development of automatic equipment and the complication of structure and properties of the garbage crusher, the fault diagnosis of garbage crusher is very important. In this paper, according to the fault symptoms and parameters, Radial Basis Function Neural Network (RBF NN) is used for fault diagnosis of the garbage crusher. The structure and inference of RBF NN are discussed in detail. The garbage crusher fault diagnosis model is established based on RBF network. At last, the fault of mechanical system is taken as an example of garbage crusher fault diagnosis. Training simulation results of the neural network are given base on MATLAB software. The result shows the RBF NN is suitable for fault diagnosis of garbage crusher.</abstract><cop>Zurich</cop><pub>Trans Tech Publications Ltd</pub><doi>10.4028/www.scientific.net/AMM.16-19.971</doi><tpages>5</tpages></addata></record> |
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title | Garbage Crusher Fault Diagnosis Based on RBF Neural Network |
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