舰船非线性配电网络的故障诊断与恢复策略研究

Research on fault diagnosis and recovery strategy of ship nonlinear distribution network

现代化的舰船配电网络非常复杂,需要兼顾到船舶上的各种用电设备。因此当配电网络出现故障时,为了能够最大程度降低故障造成的损失,需要合理控制配电网络的工作节点,隔离出现故障的子网络。本文主要采用了神经网络算法,对船舶非线性配电网络的工作模式进行训练,通过合理控制配电参数,能够有效监控网络中的故障,并提出了故障诊断算法,在故障发生时,能够自动产生恢复策略,并解决一些简单的故障,这种方式大大提高了系统的稳定性。

Modern ship distribution network is very complex,need to take into account the ship on a variety of electrical equipment.Therefore,when the distribution network fails,in order to minimize the loss caused by the failure,the need to control the distribution network of the work node,isolating the failure of the sub-network.In this paper,the neural network algorithm is used to train the working mode of the ship's nonlinear distribution network.Through the reasonable control of the distribution parameters,the fault in the network can be effectively monitored,and a fault diagnosis algorithm is proposed.When the fault occurs,generate recovery strategies,and solve some simple failures,this approach greatly improves the stability of the system.