This paper proposes an efficient learning based approach to detect the faults of an industrial oil pump.The proposed method uses the wavelet transform and genetic algorithm(GA)ensemble for an optimal feature extractio...This paper proposes an efficient learning based approach to detect the faults of an industrial oil pump.The proposed method uses the wavelet transform and genetic algorithm(GA)ensemble for an optimal feature extraction procedure.Optimal features,which are dominated through this method,can remarkably represent the mechanical faults in the damaged machine.For the aim of condition monitoring,we considered five common types of malfunctions such as casing distortion,cavitation,looseness,misalignment,and unbalanced mass that occur during the machine operation.The proposed technique can determine optimal wavelet parameters and suitable statistical functions to exploit excellent features via an appropriate distance criterion function.Moreover,our optimization algorithm chooses the most appropriate feature submatrix to improve the final accuracy in an iterative method.As a case study,the proposed algorithms are applied to experimental data gathered from an industrial heavy-duty oil pump installed in Arak Oil Refinery Company.The experimental results are very promising.展开更多
Fault current limiting is a critical technology to en sure the safe operation of modular multilevel converter based multi-terminal direct current(MMC-MTDC)grids.This paper proposes a fault severity classification base...Fault current limiting is a critical technology to en sure the safe operation of modular multilevel converter based multi-terminal direct current(MMC-MTDC)grids.This paper proposes a fault severity classification based coordination con trol strategy of fault current limiter(FCL)and MMC for adap tive fault current limiting.The proposed strategy reduces the in vestment in FCL,and keeps the bus voltages of non-faulty lines at reasonable values.Firstly,a rapid fault circuit parameter esti mation(FCPE)method using initial fault current information is proposed.With this method,the fault distance and fault transi tion resistance can be quickly estimated,which are used for a quantitative indication of the fault severity.Subsequently,the coordination control strategy of FCL and MMC is proposed,in which the FCL action is prioritized,while the control of MMC is complementary for current limiting.Based on the proposed strategy,fault severity phase planes(FSPPs)are constructed to assess fault severity and calculate the activation time of FCL and voltage regulation factor of MMC.Therefore,the FCL acti vation and MMC control are matched to the fault severity.The effectiveness and advantages of the proposed strategy are vali dated by the simulations in PSCAD/EMTDC.展开更多
文摘This paper proposes an efficient learning based approach to detect the faults of an industrial oil pump.The proposed method uses the wavelet transform and genetic algorithm(GA)ensemble for an optimal feature extraction procedure.Optimal features,which are dominated through this method,can remarkably represent the mechanical faults in the damaged machine.For the aim of condition monitoring,we considered five common types of malfunctions such as casing distortion,cavitation,looseness,misalignment,and unbalanced mass that occur during the machine operation.The proposed technique can determine optimal wavelet parameters and suitable statistical functions to exploit excellent features via an appropriate distance criterion function.Moreover,our optimization algorithm chooses the most appropriate feature submatrix to improve the final accuracy in an iterative method.As a case study,the proposed algorithms are applied to experimental data gathered from an industrial heavy-duty oil pump installed in Arak Oil Refinery Company.The experimental results are very promising.
基金supported in part by the National Natural Science Foundation of China(No.52207126)the Natural Science Foundation of Sichuan Province(No.2024NSFSC0869)the Joint Funds of the National Natural Science Foundation of China(No.U22B6006).
文摘Fault current limiting is a critical technology to en sure the safe operation of modular multilevel converter based multi-terminal direct current(MMC-MTDC)grids.This paper proposes a fault severity classification based coordination con trol strategy of fault current limiter(FCL)and MMC for adap tive fault current limiting.The proposed strategy reduces the in vestment in FCL,and keeps the bus voltages of non-faulty lines at reasonable values.Firstly,a rapid fault circuit parameter esti mation(FCPE)method using initial fault current information is proposed.With this method,the fault distance and fault transi tion resistance can be quickly estimated,which are used for a quantitative indication of the fault severity.Subsequently,the coordination control strategy of FCL and MMC is proposed,in which the FCL action is prioritized,while the control of MMC is complementary for current limiting.Based on the proposed strategy,fault severity phase planes(FSPPs)are constructed to assess fault severity and calculate the activation time of FCL and voltage regulation factor of MMC.Therefore,the FCL acti vation and MMC control are matched to the fault severity.The effectiveness and advantages of the proposed strategy are vali dated by the simulations in PSCAD/EMTDC.
