Fault recognition and coal seam thickness forecast are important problems in mineral resource prediction. Knowledge of multiple disciplines, which include mining engineering, mine geology, seismic prospecting etc, was...Fault recognition and coal seam thickness forecast are important problems in mineral resource prediction. Knowledge of multiple disciplines, which include mining engineering, mine geology, seismic prospecting etc, was used synthetically. Artificial neural network was combined with genetic algorithm to found integrated AI method of genetic algorithm artificial neural network(GA ANN). Fault recognition and coal seam thickness forecast were carried to completion by case studies. And the research results are satisfactory.展开更多
The prominence of Renewable Energy Sources(RES)in the process of power generation is exponentially increased in the recent days since these sources assist in minimizing the environmental contamination.A grid-tied DFIG...The prominence of Renewable Energy Sources(RES)in the process of power generation is exponentially increased in the recent days since these sources assist in minimizing the environmental contamination.A grid-tied DFIG(Doubly Fed Induction Generator)based WECS(Wind Energy Conversion System)is introduced in this work,in which a Landsman converter is implemented to impro-vise the output voltage of PV without anyfluctuations.A novel GA(Genetic Algorithm)assisted ANN(Artificial Neural Network)is employed for tracking the Maximum power from PV.Among the rotor and grid side controllers,the for-mer is implemented by combining the statorflux with d-q reference frame and the latter is realized by the PI controller.The proposed approach delivers better per-formance in the compensation of real and reactive power along with the DC link voltage control.The controlling mechanism is verified in both MATLAB and experimental bench setupby using an emulated wind turbine for the concurrent control of DC link potential,active and reactive powers.The source current THD is observed as 1.93%and 2.4%for simulation and hardware implementation respectively.展开更多
基金National Natural Science Foundation of China(5 97740 0 5 )
文摘Fault recognition and coal seam thickness forecast are important problems in mineral resource prediction. Knowledge of multiple disciplines, which include mining engineering, mine geology, seismic prospecting etc, was used synthetically. Artificial neural network was combined with genetic algorithm to found integrated AI method of genetic algorithm artificial neural network(GA ANN). Fault recognition and coal seam thickness forecast were carried to completion by case studies. And the research results are satisfactory.
文摘The prominence of Renewable Energy Sources(RES)in the process of power generation is exponentially increased in the recent days since these sources assist in minimizing the environmental contamination.A grid-tied DFIG(Doubly Fed Induction Generator)based WECS(Wind Energy Conversion System)is introduced in this work,in which a Landsman converter is implemented to impro-vise the output voltage of PV without anyfluctuations.A novel GA(Genetic Algorithm)assisted ANN(Artificial Neural Network)is employed for tracking the Maximum power from PV.Among the rotor and grid side controllers,the for-mer is implemented by combining the statorflux with d-q reference frame and the latter is realized by the PI controller.The proposed approach delivers better per-formance in the compensation of real and reactive power along with the DC link voltage control.The controlling mechanism is verified in both MATLAB and experimental bench setupby using an emulated wind turbine for the concurrent control of DC link potential,active and reactive powers.The source current THD is observed as 1.93%and 2.4%for simulation and hardware implementation respectively.
