Humidity Drift Modeling and Compensation of MEMS Gyroscope Based on IAWTD-CSVM-EEMD Algorithms

Abstract

A novel fusion algorithm is proposed based on Improved Adaptive Wavelet Threshold De-noising (IAWTD), C-means Support Vector Machine (CSVM) and Ensemble Empirical Mode Decomposition (EEMD) method to eliminate the humidity drift of MEMS gyroscope. Firstly, the IAWTD method is employed to decrease the humidity drift component in MEMS gyroscope output signal. Then, the humidity drift compensation model is established: the input elements are the relative humidity, the change rate of relative humidity and the humidity drift, and the output is the compensated MEMS gyroscope output signal by EEMD method. In order to verify the compensation effect of the fusion algorithm, the gyroscope outputs are collected and analyzed with the relative humidity ranged from 40% to 90% based on the temperature varying from 20°C to 60°C. The results show that the IAWTD-CSVM-EEMD method significantly reduces the influence of relative humidity drift on the gyroscope output, according to the quantitative analysis of Allan variance, the quantization noise of the gyroscope output decreases by 87.78%, 96.37%, 97.77%, 99.17% and 92.62% respectively under the relative humidity ranging from 40% to 90%, as the temperature rose from 20 °C to 60 °C at intervals of 10 °C. In addition, the bias stability decreases by 96.9%, 99.41%, 99.1%, 99.46%, and 99.78% respectively and the angle random walk decreases by 88.16%, 96.54%, 98.16%, 94.43%, and 92.05% respectively at different temperatures. It is worth mentioning that, to further verify the applicability of the fusion algorithm, a group of comparative experiments are added to consider the influence of temperature changes on the gyroscope output under different relative humidity. The experimental results show that the quantization noise, bias stability and angle random walk of the MEMS gyroscope are significantly reduced compared with the original output after processing by IAWTD-CSVM-EEMD. Therefore, the method proposed in this paper is beneficial to reduce the humidity drift in the MEMS gyroscope output.

Keywords

• MEMS gyroscope
• relative humidity
• humidity drift model
• Allan variance