XIE Yan, LI Ping, JIANG Hong. Application of big data analytics approach in wind tunnel test[J]. 2019, 37(6): 1004-1009.DOI: 10.7638/kqdlxxb-2018.0105.
Application of big data analytics approach in wind tunnel test
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.
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references
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