机理-数据融合驱动的互联变流系统故障诊断方法OACSTPCD

Three-level neutral-point-clamped(3L-NPC)interconnected converters have been widely used in the AC-DC hybrid distribution grids due to their superiorities of large capacity and high power quality.However,their working conditions are always with high power,varying load,and limited heat dissipation,etc.,with a high open-circuit failure rate of power switches.Meanwhile,existing fault diagnosis methods are mostly single mechanism-based or data-based,unable to overcome the problems of complex system model structure and changing operating conditions,resulting in low diagnostic accuracy and speed.To this end,a mechanism-data-fusion-driven fault diagnosis method for interconnected conversion systems was proposed.Firstly,a mechanism-data-fusion model was constructed using a neural network observer to improve the fault diagnosis accuracy.Subsequently,the trajectories of current residuals after open-circuit faults of different devices were analyzed,and a current residual table was summarized,based on which a fast and accurate open-circuit fault diagnosis method was formed.Finally,the experimental and hardware-in-the-loop results verify the effectiveness of the proposed method.