Calibration of multihole aerodynamic pressure probe is a compulsory and important step in applying this kind of probe. This paper presents a new neural-network-based method for the calibration of such probe. A new type of evolutionary algorithm, i.e., differential evolution (DE), which is known as one of the most promising novel evolutionary algorithms, is proposed and applied to the training of the neural networks, which is then used to calibrate a multihole probe in the study. Based on the measured probe’s calibration data, a set of multilayered feed-forward neural networks is trained with those data by a modified differential evolution algorithm. The aim of the training is to establish the mapping relations between the port pressures of the probe being calibrated and the properties of the measured flow field. The proposed DE method is illustrated and tested by a real case of calibrating a five-hole probe. The results of numerical simulations show that the new method is feasible and effective.
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January 2003
Technical Papers
An Improved Neural-Network-Based Calibration Method for Aerodynamic Pressure Probes
Hui-Yuan Fan,
Hui-Yuan Fan
Department of Building and Construction, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong, HKSAR, P. R. China
SER Turbomachinery Research Center, School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, P. R. China
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Wei-zhen Lu,
Wei-zhen Lu
Department of Building and Construction, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong, HKSAR, P. R. China
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Guang Xi,
Guang Xi
SER Turbomachinery Research Center, School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, P. R. China
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Shang-jin Wang
Shang-jin Wang
SER Turbomachinery Research Center, School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, P. R. China
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Hui-Yuan Fan
Department of Building and Construction, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong, HKSAR, P. R. China
SER Turbomachinery Research Center, School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, P. R. China
Wei-zhen Lu
Department of Building and Construction, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong, HKSAR, P. R. China
Guang Xi
SER Turbomachinery Research Center, School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, P. R. China
Shang-jin Wang
SER Turbomachinery Research Center, School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, P. R. China
Contributed by the Fluids Engineering Division for publication in the JOURNAL OF FLUIDS ENGINEERING. Manuscript received by the Fluids Engineering Division Jan. 6, 2001; revised manuscript received July 29, 2002. Associate Editor: A. K. Prasad.
J. Fluids Eng. Jan 2003, 125(1): 113-120 (8 pages)
Published Online: January 22, 2003
Article history
Received:
January 6, 2001
Revised:
July 29, 2002
Online:
January 22, 2003
Citation
Fan, H., Lu, W., Xi , G., and Wang, S. (January 22, 2003). "An Improved Neural-Network-Based Calibration Method for Aerodynamic Pressure Probes ." ASME. J. Fluids Eng. January 2003; 125(1): 113–120. https://doi.org/10.1115/1.1523063
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