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.