Python-based cubic B-spline interpolation algorithm for pump characteristic curves

• Main Authors: Zhang, Yang, Wang, Lei, Zhao, Jiang, Yao, Wei
• Format: Conference Proceeding
• Language: English
• Published: SPIE 16.06.2023
• ISBN: 9781510664890; 1510664890
• ISSN: 0277-786X
• DOI: 10.1117/12.2681838

The pump characteristic curve is fitted by discrete test points, which is a curve reflecting the inner connection and change laws of performance parameters such as flow, head, and efficiency of the pump, and its accuracy and reliability have a significant influence on its selection and use. This paper designs a cubic B-spline interpolation algorithm, and then conducts a comparative study of the interpolation algorithm and the least squares polynomial fitting method of different orders through experiments and Python programming. The experimental results show that the cubic B-spline interpolation method not only can more accurately describe the variation of the pump characteristic curve under both small and large flow conditions, but also avoid the phenomenon that the curve is not smooth enough and the data does not fit when the least squares method is used to fit the curve, which is of high application value in scientific research and engineering applications.