船舶电力系统集成了发电、电力转换、电力传输和配置等功能，为船舶自动化电气、照明、导航等系统提供能源，是船舶必不可少的基础系统。由于船舶电力系统的工况复杂，环境恶劣，电力系统的故障率比较高。针对这一问题，本文结合电力系统的关键元件建模，开发了基于神经网络算法的船舶电力系统故障诊断方法，介绍了故障诊断的流程，并基于Windows 7平台开发了船舶电力系统故障在线监测系统，可以在线监测电力系统的功率谱、电流等参数。
Ship power system integrates the functions of power generation, power conversion, power transmission and configuration, and provides energy for ship automation, electrical, lighting, navigation and other systems. It is an essential basic system for ships. Due to the complex working conditions and harsh environment of ship power system, the failure rate of power system is relatively high. To solve this problem, combined with the modeling of key components of power system, this paper develops the fault diagnosis method of ship power system based on neural network algorithm, introduces the process of fault diagnosis, and develops the on-line fault monitoring system of ship power system based on Windows 7 platform, so that ship operators can monitor the power spectrum, current and other parameters of power system on-line.
2022,44(11): 132-135 收稿日期：2021-12-21
DOI：10.3404/j.issn.1672-7649.2022.11.027
分类号：U622.24
基金项目：咸阳市重点研发项目(2019k02-20)
作者简介：朱赖红(1975-)，男，硕士，讲师，主要研究方向为计算机软件及系统集成
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