船舶电泵是发电系统中的关键组成部分，传统电泵维修和监测主要依靠人工经验，存在很大的局限性，电泵故障数据量庞大，嵌入式平台难以建立电泵故障分析模型并对故障数据进行分析。本文对4G无线网络传输技术以及大数据技术的基本原理进行研究，设计基于大数据技术的船舶发电系统电泵故障监测系统架构，分析系统各个部分的基本功能；使用云平台计算实现了电泵故障数据的分布式存储和计算，以电泵电流平均值计算为例，分析分布式计算的实现过程。电泵故障监控系统基于大数据平台具有良好的扩展性和可靠性。
Marine electric pump is a key component of the power generation system. The traditional maintenance and monitoring of electric pump mainly rely on manual experience, which has great limitations, and the embedded platform is difficult to establish the electric pump fault analysis model and analyze the fault data. In this paper, the basic principles of 4G wireless network transmission technology and big data technology are fully studied, and the electric pump fault monitoring system architecture based on big data technology is designed, and the basic functions of each part of the system are analyzed. The distributed storage and calculation of electric pump fault data are realized by using cloud platform. The process of distributed calculation is analyzed by taking the average current calculation of electric pump as an example. Electric pump fault monitoring system based on big data platform has good scalability and reliability.
2023,45(20): 151-154 收稿日期：2023-6-3
DOI：10.3404/j.issn.1672-7649.2023.20.028
分类号：U667.65
基金项目：舟山市科技局市级公益类项目（2023C31058）
作者简介：俞凯耀(1988-),男,硕士,讲师,研究方向为智能控制、热工控制及自动化控制等
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