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DATA MODELING METHOD BASED ON PARTIAL LEAST SQUARE REGRESSION AND APPLICATION IN CORRELATION ANALYSIS OF THE STATOR BARS CONDITION PARAMETERS
作者姓名:李锐华  高乃奎  谢恒堃  史维祥
作者单位:[1]DepartmentofMechatronicsengineering,Xi'anJiaotongUniversity,Xi'an710049,China [2]StateKeyLaboratoryofElectricalInsulationforPowerEquipment,Xi'anJiaotongUniversity,Xi'an710049,China [3]DepartmentofMechatronicsengineering,Xi'anJiaotongUniversity,Xi'an710049,China
基金项目:ThisresearchwassupportedbytheKeyTechnologiesR&DProgramofStatePowerCorporationofChinaDuringtheTenthFiveYearPlanPeriod(No.SP1120010112)
摘    要:Objective To investigate various data message of the stator bars condition parameters under the condition that only a few samples are available, especially about correlation information between the nondestructive parameters and residual breakdown voltage of the stator bars. Methods Artificial stator bars is designed to simulate the generator bars. The partial didcharge(PD) and dielectric loss experiments are performed in order to obtain the nondestructive parameters, and the residual breakdown voltage acquired by AC damage experiment. In order to eliminate the dimension effect on measurement data, raw data is preprocessed by centered-- compress. Based on the idea of extracting principal components, a partial least square (PLS) method is applied to screen and synthesize correlation information between the nondestructive parameters and residual breakdown voltage easily. Moreover, various data message about condition parameters are also discussed. Results Graphical analysis function of PLS is easily to understand various data message of the stator bars condition parameters. The analysis Results are consistent with result of aging testing. Conclusion The method can select and extract PLS components of condition parameters from sample data, and the problems of less samples and malticollinearity are solved effectively in regression analysis.

关 键 词:PCA  偏最小二乘方  状态参数  定子绕组

DATA MODELING METHOD BASED ON PARTIAL LEAST SQUARE REGRESSION AND APPLICATION IN CORRELATION ANALYSIS OF THE STATOR BARS CONDITION PARAMETERS
Li Ruihua,Gao Naikui,Xie Hengkun,Shi Weixiang.DATA MODELING METHOD BASED ON PARTIAL LEAST SQUARE REGRESSION AND APPLICATION IN CORRELATION ANALYSIS OF THE STATOR BARS CONDITION PARAMETERS[J].Academic Journal of Xi’an Jiaotong University,2004,16(2):127-131.
Authors:Li Ruihua  Gao Naikui  Xie Hengkun  Shi Weixiang
Institution:1. Department of Mechatronics engineering, Xian Jiaotong University, Xi'an 710049, China.
2. State Key Laboratory of Electrical Insulation for Power Equipment, Xi'an Jiaotong University, Xi'an 710049, China.
Abstract:Objective To investigate v arious data message of the stator bars condition parameters under the condition that only a few samples are available, especially about correlation information between the nondestructive parameters and residual breakdown voltage of the stat or bars. Methods Artificial stator bars is designed to simulat e the generator bars. The partial didcharge( PD) and dielectric loss experiments are performed in order to obtain the nondestructive parameters, and the residua l breakdown voltage acquired by AC damage experiment. In order to eliminate the dimension effect on measurement data, raw data is preprocessed by centered-compr ess. Based on the idea of extracting principal components, a partial least squar e (PLS) method is applied to screen and synthesize correlation information betwe en the nondestructive parameters and residual breakdown voltage easily. Moreover , various data message about condition parameters are also discussed. Re sults Graphical analysis function of PLS is easily to understand vario us data message of the stator bars condition parameters. The analysis Results ar e consistent with result of aging testing. Conclusion The meth od can select and extract PLS components of condition parameters from sample dat a, and the problems of less samples and multicollinearity are solved effectively in regression analysis.
Keywords:partial least square  PCA  condition parameter  s tator winding
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