柴油机是船舶推进系统的重要组成部分，随着柴油机技术的不断发展，对柴油机相关参数进行监测并分析是必然发展趋势。柴油机的故障监测需要依赖大量的柴油机监测数据，而嵌入式处理器无法实现大量监测数据的实时采集和分析。本文提出一种基于Hadoop技术的船舶柴油机大数据处理平台，对Hadoop技术的HDFS和MapReduce的实现原理进行详细分析。在此基础上设计系统的整体结构框图，并对多文件的写入速度和数据排序进行测试。本文基于Hadoop技术的船舶柴油机大数据平台可以满足船舶柴油机数据的存储和分析需求，并且具有较高的可靠性和扩展性。
Diesel engine is an important part of marine propulsion system. With the continuous development of diesel engine technology, it is an inevitable trend to monitor and analyze related parameters of diesel engine in the future. The fault monitoring of diesel engine depends on a large number of diesel engine monitoring data, and embedded processor can not realize the real-time collection and analysis of a large number of monitoring data. In this paper, a big data processing platform for marine diesel engine based on Hadoop technology is proposed, and the implementation principle of HDFS and MapReduce of Hadoop technology is analyzed in detail. On this basis, the overall structure diagram of the system is designed, and the writing speed of multiple files and data sorting are tested. The big data platform of marine diesel engine with Hadoop technology designed in this paper can meet the storage and analysis requirements of marine diesel engine data, and has high reliability and scalability.
2023,45(11): 119-122 收稿日期：2023-01-08
DOI：10.3404/j.issn.1672-7619.2023.11.023
分类号：U667.65
作者简介：吕志峰(1977-),男,工程师,研究方向为船舶通信技术、数据挖掘及网络技术
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