Optimization of temperature compensation model on angle sensor based on nonlinear fitting

Abstract

In industrial measurement, the accuracy of accelerometer is much sensitive to the change of environmental temperature. Although previous work can achieve good performance about reducing the temperature impact, all of them cannot achieve a high accuracy. A new nonlinear fitting method is proposed to eliminate temperature influence on the accuracy of accelerometer. When using an accelerometer to calculate an object’s tilt angle, the change of temperature will lead to drift on the value of accelerometer. This drift will lead to the increase of angle calculation bias. In order to solve this problem, this paper proposes a new experimental nonlinear fitting temperature compensation method. With the measurement data and the quadratic model evolution, this method can effectively eliminate the influence of temperature on the accuracy of accelerometer and improve the precision and the accuracy of angle calculating. The experimental results show that this method has an advantage of high compensation accuracy.