面向海量数据的全船振动分析管理系统研究
2022,30(10):202-208
摘要：目前广泛采用的振动测试系统侧重于数据采集的精度、采样率等指标的提高，但数据预处理环节不足，智能化程度不高，测试人员面对分散数据，查询对比分析存在很大困难；为集中有效管理海量预处理数据，实现数据高性能查询分析，分别设计了面向查询结果和面向数据解耦关系的两套数据库；采用MySQL + Python架构实现了海量数据背景下全船振动数据的快速查询与分析等功能；经过多艘船舶的数据处理实践表明，该系统有效解决了振声数据的综合分析问题，具有一定的工程实际应用价值。
关键词：海量数据;振动噪声 关系型数据库;混合编程
Research on Whole Ship Vibration Analysis and Management System for Massive Data
Abstract：At present, the widely used vibration test system focuses on the improvement of data acquisition accuracy, sampling rate and other indicators, but the data preprocessing link is insufficient and the degree of intelligence is not high. In the face of scattered data, the test personnel have great difficulties in query and comparative analysis. In order to manage massive preprocessed data effectively and realize high performance query and analysis of data, two databases oriented to query results and data decoupling are designed respectively. The MySQL + Python architecture is used to realize the rapid query and analysis of ship vibration data under the background of massive data. The data processing practice of several ships shows that the system effectively solves the comprehensive analysis problem of vibration and sound data, and has certain engineering practical application value.
Key words：Massive data; vibration noise; relational database; hybrid programming
收稿日期：2022-04-13
基金项目：国家自然科学基金(11974429)
