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  • E-ISSN2508-7894
  • KCI

A Study on Improving Pressure Sensor Calibration Based on Multiple Calibration Points and Auto Target Setting*

Korean Journal of Artificial Intelligence / Korean Journal of Artificial Intelligence, (E)2508-7894
2024, v.12 no.4, pp.35-42
https://doi.org/10.24225/kjai.2024.12.4.35
Jonghyun OH (Daejeon University)
Jae-Yong HWANG (Daejeon University)
Tumenbat TENGIS (Daejeon University)
Woo-Seong JUNG (Daejeon University)

Abstract

Pressure sensors are essential equipment for precise measurements in industrial and research fields, requiring calibration and target value setting for each sample to ensure high accuracy. This study proposes an automated target value prediction method based on a polynomial regression model to enhance pressure sensor accuracy and evaluates its effectiveness. Experiments were conducted over a pressure range of 0 to 45 bar and a temperature range of -5°C to 60°C. By expanding the calibration points from the previous two to four, linearity error was improved from 0.380% to 0.116%. In the conventional method, theoretical output values were manually calculated based on LDO voltage, and target values were set accordingly. However, this study employed a method that uses Polynomial Features (degree=2) transformation followed by a Linear Regression model to automatically predict target values. This approach allowed samples to more precisely follow the target voltage. This study demonstrates that an automated target value setting with multiple calibration points can contribute to improving the accuracy of pressure sensor measurements.

keywords
Pressure sensors, Calibration, Auto target, Points, LDO, Linear Regression
Submission Date
2024-10-14
Revised Date
2024-11-07
Accepted Date
2024-12-05

Korean Journal of Artificial Intelligence