Research on compensation method for registration error of large-scale measurement field based on multi-temperature sensors

Abstract

Purpose The size of the aircraft tooling structure is huge, and the ambient temperature is difficult to maintain a constant state. Aiming at the influence of current temperature, this paper aims to propose a compensation method for registration error of large-scale measurement fields based on multi-temperature sensors. Design/methodology/approach In this method, an enhanced reference points (ERS)–temperature regression model is constructed from ERS and temperature data. The ERS offsets compensation model is established by solving the offset through the regression model, and the ERS offset compensation analysis is carried out. Findings The experimental results show that the proposed registration error compensation algorithm has obvious advantages over traditional methods in reducing the influence of ambient temperature and improving the measurement accuracy by reducing the registration error. Originality/value This method reduces registration error caused by the influence of ambient temperature and is used for aircraft measurements in different temperature environments.

Dynamic compensation by coupled triple-thermocouples for temperature measurement error of high-temperature gas flow

“…Here are some examples of these intelligent compensation methods. The compensation method that supports vector machine (Yu et al, 2017), Robust machine tool thermal error compensation method for CNC machine machining process (Liu et al, 2020), segmentation compensation method for FOG temperature error based on particle swarm optimization algorithm (Tong et al, 2019), compensation method based on enhanced reference points (ERS)-temperature regression model (Huang et al, 2022), and two-thermocouple sensor characterization method (Hung et al, 2008).…”