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| Improved Grey Evaluation Method for Uncertainty of Minimum Sample Data |
| ZHU Yan-long1,2,CHENG Yin-bao1,GAO Hong-tang1,2,WANG Yan3,SHI Jiang-huan4,LUO Zai1,LI Ya-ru1 |
1. China Jiliang University, Hangzhou , Zhejiang 310018, China
2. National Institute of Metrology, Beijing 100029, China
3.Shenyang Aircraft Industry (Group) Co., Ltd, Shenyang, Liaoning 110850, China
4. Ningbo Institute of Metrology and Testing, Ningbo, Zhejiang 315048, China |
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Abstract In order to solve the limitation problem of the classical grey assessment model of measurement uncertainty under the condition of very small sample, SMOTE technique and SVR model are introduced on the basis of analyzing the principle of the classical model. Then, an improved grey evaluation method of measurement uncertainty is proposed after applicability modification. Finally, the computer simulation data and the total temperature data from the air flow measurement of an aero-engine high-altitude simulation experiment are applied to the model to verify the reliability and generalization of the model. The results show that the improved grey method can adapt to the minimum sample size data of different distribution types with the calculation results of the range method as a reference. The maximum improvement is 41.18% in the simulation data and 50.00% in the instance data.Therefore, this improved grey method may be an effective way to solve the uncertainty evaluation of very small sample data.
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Received: 10 April 2023
Published: 27 December 2023
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2023, Vol. 44 
