谢艳, 李平, 蒋鸿. 大数据分析方法在风洞试验中的应用[J]. 空气动力学学报, 2019, 37(6): 1004-1009. DOI: 10.7638/kqdlxxb-2018.0105
引用本文: 谢艳, 李平, 蒋鸿. 大数据分析方法在风洞试验中的应用[J]. 空气动力学学报, 2019, 37(6): 1004-1009. DOI: 10.7638/kqdlxxb-2018.0105
XIE Yan, LI Ping, JIANG Hong. Application of big data analytics approach in wind tunnel test[J]. ACTA AERODYNAMICA SINICA, 2019, 37(6): 1004-1009. DOI: 10.7638/kqdlxxb-2018.0105
Citation: XIE Yan, LI Ping, JIANG Hong. Application of big data analytics approach in wind tunnel test[J]. ACTA AERODYNAMICA SINICA, 2019, 37(6): 1004-1009. DOI: 10.7638/kqdlxxb-2018.0105

大数据分析方法在风洞试验中的应用

Application of big data analytics approach in wind tunnel test

  • 摘要: 针对风洞常规试验采用阶梯抽样采集的方法,得到的试验数据和信息较少,导致试验数据分析和试验故障分析困难的问题,尝试在风洞常规试验中构建起风洞试验大数据的采集、收集和分析处理平台,并利用大数据较强的洞察能力,助力风洞试验中的疑难问题的分析。主要通过将风洞采集方法改为连续采集试验全程数据,开发杂混数据的通用风洞试验数据处理程序,开发海量试验数据分析显示软件等步骤,搭建起风洞试验大数据综合处理系统。并通过此平台对风洞试验大数据进行挖掘计算,使隐含的有用信息显现出来,为试验数据和试验故障深入分析指明方向。该平台在2 m量级的高速风洞试验中的应用表明,此系统实现了风洞试验全程全部试验数据信息的采集,实现了风洞试验大数据的处理分析和结果展示。通过大数据分析有助于快速理清常规试验中的疑难问题。通过对风洞传统采集、处理方法的改进,实现了风洞试验从传统的阶梯抽样采集的小数据时代到采集全部试验数据信息的大数据时代的转变。从风洞试验大数据中获取的频率、概率、相关关系等数据可以为故障的定位分析、事件因果关系的分析等提供有力的数据支持。

     

    Abstract: The traditional wind tunnel test adopts conventional pitch-and-pause testing mode and get less test data and information, which leads to difficulties in the analysis of test data and analysis of test failures. It is attempted to establish acquisition, analysis, and processing platform of big data for wind tunnel tests and make use of the powerful insights of big data to help analyze the difficult problems in wind tunnel tests. The wind tunnel test big data synthesis processing system can be built mainly through changing the acquisition method of wind tunnel to the method of continuous collection of all test data throughout the test, by developing general wind tunnel test data processing program for hybrid data and massive test data analysis and display software and other steps. Through this platform, excavation calculation is performed on large-scale wind tunnel test data, so that useful and implicit information is revealed, and the direction for in-depth analysis of test data and experimental failures is pointed out. The application of the system in 2 meter-scale high-speed wind tunnel test indicates that the platform has achieved the entire collection of wind tunnel test data, processing and analysis of wind tunnel test big data, and results display. The analysis results can help us quickly clarifying many issues that have troubled us. Through the improvement of conventional collection and process methods for wind tunnel test data, the wind tunnel test has changed from the traditional small-data acquisition of pitch-and-pause sampling to the big data era of collecting all test data information. The frequency, probability, correlation, etc. obtained from wind tunnel test big data can provide powerful data support for fault location analysis and event causality analysis.

     

/

返回文章
返回