利用主成分分析方法对海上采集的数据进行压缩,实现船舶远程诊断和维护

I. Sotés, J. L. Larrabe, Miguel A. Gomez, F. J. Alvarez, M. C. Rey-Santano, V. Mielgo, E. Gastiasoro
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引用次数: 0

摘要

在海上,语音和数据通信通过卫星几乎覆盖全球。卫星通信正在增加带宽和降低成本,但与地球上的水平仍有很大差距。主成分分析(PCA)是一种用于有损或非精确压缩数据的统计技术;是多维数据集模式搜索的常用工具。本研究的断言是使用PCA理论压缩的可能性,具有足够的准确性,船上收集的大量数据,然后通过卫星发送它们,以比传统更便宜或/和更快的方式。该策略适用于船舶地面设备远程诊断和维修决策。因此,大大节省了电信成本和电信时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Telediagnosis and maintenance of the ship from land, using principal component analysis to compress acquired data offshore
At sea, voice and data communications have virtually global coverage via satellite. Satellite communications are increasing the bandwidth and lowering the cost, but are still far from levels that are in earth. The Principal components analysis (PCA) is a statistical technique used for lossy or non exact compression data; is a common tool for the search of pattern of multidimensional data sets. The assertion of this study was the possibility of using the PCA theory to compress, with sufficient accuracy, the large amount of data that are collected on board, and then send them all via satellite, in a cheaper or/and faster way than traditionally. This strategy is appropriate for decision making about telediagnosis and maintenance of the ship using ground equipment. Consequently, significant savings are achieved in telecommunication costs and telecommunication times.
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