ERRORS REDUCTINON OF MEASUREMENT DEVICE BY USING AKIMA INTERPOLATION
Abstract
Akima interpolation is an effective tool for signal processing in many problems such as data preprocessing for machine learning models, modeling and simulation data generation and post-processing of sensor data for measurement and control problems. In the field of measurement, most sensors are given in the form of value tables, so they have a finite number of known values and often have nonlinear characteristics, causing large measurement errors, especially in rapidly changing environments. The nature of Akima interpolation is a polynomial interpolation method, which estimates the value of a function at points between known data points, thus providing the ability to continuously characterize the measurement characteristics of the measuring device. This paper will apply the Akima interpolation method to correct errors in temperature measurement. The ability to improve measurement accuracy has been verified by Matlab simulation software and surveying the measurement results of a manufactured experimental temperature measuring device. The measurement error correction algorithm proposed in this study can also be effectively applied to other measured quantities, contributing to diversifying solutions to reduce measurement errors.
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