Application of neural networks to fluid measurements with a five-hole probe

被引：0

作者：

Uelschen, M ^{[1
]}

Weidenfeller, J ^{[1
]}

Lawerenz, M ^{[1
]}

机构：

[1] Univ Gesamthsch Kassel, Fachbereich Maschinenbau, Inst Therm Energietech, Fachgebiet Stromungsmaschinen, D-34125 Kassel, Germany

来源：

TECHNISCHES MESSEN | 1999年 / 66卷 / 10期

关键词：

D O I：

暂无

中图分类号：

TH7 [仪器、仪表];

学科分类号：

0804 ; 080401 ; 081102 ;

摘要：

For determining the velocity vector with a five-hole pressure probe without rotation around the axis a previous calibration is necessary. A polynom is usually used for the analysis of the calibration. For getting a sufficient accuracy a minimum number of calibration points is needed for approximating the polynom coefficients. The paper describes a method based on artificial neural network which reduces the number of calibration points while simultaneous increase of the accuracy.

引用

页码：372 / 377

页数：6

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