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Prognostic methodology for health management of electrical equipments of propulsion system in a type of vessel based on artificial immune algorithm

机译:基于人工免疫算法的船舶动力系统电气设备健康管理的预测方法

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The propulsion system of a vessel is the key facility to guarantee its safe sail and reliable implementation. However there is a complex network of electrical equipments in the propulsion system, in which every component should be reliable enough in order to guarantee the vessel always running in a well health state. In this paper, in view of the health management of electrical equipments of propulsion system in a type of vessel, a prognostic methodology of health state is proposed based on artificial immune algorithm. Some hazard devices which have high probability to cause the system into failure and their monitored order which can be computed based on their hazard degree to system and affinity to fault devices, can both be acquired on the basis of some failure data and current data via artificial immune algorithm. Meanwhile, some parameters of these devices which should be specially monitored can also be obtained to help operators predict the failure of system. This paper will also employ some failure data from electrical equipments of propulsion system in a type of vessel and some simulative data to demonstrate how artificial immune algorithm can be applied in prognosis of this electrical system.
机译:船舶的推进系统是确保其安全航行和可靠实施的关键设施。但是,推进系统中有复杂的电气设备网络,其中每个组件都应足够可靠,以确保船舶始终处于良好的健康状态。针对一类船舶推进系统电气设备的健康管理问题,提出了一种基于人工免疫算法的健康状态预测方法。可以基于一些故障数据和当前数据,通过人工获取一些可能导致系统故障的危险设备及其监视顺序,可以根据它们对系统的危险程度和对故障设备的亲和性来计算它们的监视顺序。免疫算法。同时,还可以获得这些设备的一些参数,这些参数应该进行专门监视,以帮助操作员预测系统故障。本文还将利用来自某类型船舶的推进系统电气设备的一些故障数据和一些模拟数据,来证明如何将人工免疫算法应用于该电气系统的预后。

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