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《Bearing》 2009-02
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Dynamic Forecast of Temperature State for Water Feeding Pump Bearings

WU Xing-wei1,2,CHI Dao-cai1(1.Shenyang Agriculture University,Shenyang 110161,China;2.Shenyang Institute of Engineering,Shenyang 110136,China)  
In order to forecast the temperature state of water feeding pump bearings and increase the operating safety and economy of water feeding pump,the kernel algorithm of Statistical Learning Theory(SLT),Support Vector Machine(SVM),is applied to set up a forecast model of water feeding pump bearing temperature.The model based on SVAR is compared with the model based on Gray Model and the model based on Autoregressive by a case.The result indicate that the forecast model of water feeding pump bearing temperature based on SVAR have many advantage,such as high precision,high calculation velocity,modeling easily.The model based on SVAR can forecast the bearing temperature condition of water feeding pump in operation,and avoid the fault due to the bearing temperature variety.
【Fund】: 水利部“948”科技创新项目(CT200516);; 辽宁省教育厅科技公关项目(05L385)
【CateGory Index】: TK223.5
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