A method to reduce the error of ice shape test

By conducting multiple repetitive tests in icing wind tunnel tests and using BLSOM neural network and Kriging regression model to process point cloud data, the problem of large ice shape error in icing wind tunnel tests was solved, and the ice shape error was significantly reduced and the accuracy was improved.

CN119043635BActive Publication Date: 2025-09-23AVIC GENERAL HUANAN AIRCRAFT IND CO LTD
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Patent Information

Application Number
CN202411145237.9
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2024-08-20
Publication Date
2025-09-23
Estimated Expiration
2044-08-20

AI Technical Summary

Technical Problem

There are large repeatability errors in icing wind tunnel tests, and existing technologies are difficult to effectively reduce ice shape errors, which affects test accuracy.

Method used

Multiple repetitive tests were carried out on the same test model and under the same icing conditions. Point cloud data was acquired using a 3D digital scanner. The point cloud data was processed using a clustering algorithm based on a BLSOM neural network and a Kriging regression model. The two-dimensional average ice shape and its tolerance band were calculated to reduce errors.

Benefits of technology

Significantly reduce the random error of a single test, improve the stability and accuracy of the test results, provide quantitative error description, and achieve standardization and normalization of ice shape description.

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Abstract

The present invention provides a method for reducing test ice shape errors, comprising conducting n repetitive icing wind tunnel tests under the same test model and icing conditions; placing n sets of acquired three-dimensional test ice shape point cloud data in the same data space under the same position reference conditions, thereby overlapping the n sets of point cloud data; projecting the overlapped point cloud data onto a two-dimensional plane along the model height direction to obtain two-dimensional overlapping point cloud data; clustering the data to obtain a two-dimensional average ice shape; calculating a tolerance band for the two-dimensional average ice shape; using the two-dimensional average ice shape and its tolerance band combination to quantitatively describe the target ice shape; and performing regression interpolation on characteristic points on the ice shape curve to obtain a smooth parameterized ice shape curve that filters out noise points on the numerical ice shape curve. The present invention can reduce the error of three-dimensional test ice shape and improve the accuracy of icing wind tunnel tests, with lower cost, simpler operation, clearer theory, greater practicality, and more significant results.
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