Abstract
The conventional temperature drift error (TDE) compensation model cannot decouple temperature dependence of Si-based materials because temperature correlated quantities (TCQ) have not been obtained comprehensively, and Micro-Electro-Mechanical System gyros’ (MEMS-gyros’) environmental adaptability is reduced in diverse, complicated conditions. The study presents modification of TDE compensation model of MEMS-gyros based on microstructure thermal effect analysis (MTEA). First, Si-based materials’ temperature dependence was studied in microstructure with thermal expansion effect and TCQ that determines the structural deformation were extracted to modify the conventional model, including temperature variation and its square. Second, a precise TDE test method was formed by analyzing heat conduction process between MEMS-gyros and thermal chamber, and temperature experiments were designed and conducted. Third, the modified model’s parameters were identified based on radical basis function artificial neural network (RBF ANN) and its performance was evaluated. Last, the conventional and modified models were compared in performance. The experimental results show MEMS-gyros’ bias stability was up to 10% of the conventional model, the temperature dependence of Si-based materials was decoupled better by the modified one and the environmental adaptability of MEMS-gyros was improved to expand their application in diverse complicated conditions.
Highlights
With the progress of science and technology, humans’ willingness to explore space and develop resources is increasing [1,2,3,4,5,6,7]
The experimental results show MEMS-gyros’ bias stability was up to 10% of the conventional model, the temperature dependence of Si-based materials was decoupled better by the modified one and the environmental adaptability of MEMS-gyros was improved to expand their application in diverse complicated conditions
This results in attitude errors, velocity errors and heading errors accumulating over time, and some wrong references are given to unmanned intelligent devices
Summary
With the progress of science and technology, humans’ willingness to explore space and develop resources is increasing [1,2,3,4,5,6,7]. Taking the accuracy of MEMS-gyro into account (±0.00875◦ /s) for example, when ambient temperature varies by 10 ◦ C, its TDE is about 0.7◦ /s [13] This results in attitude errors, velocity errors and heading errors accumulating over time, and some wrong references are given to unmanned intelligent devices. Based on a number of test data, Bourgeteau et al concluded complex nonlinearity appeared between ambient temperature and TDE, and describing it accurately was a prerequisite to TDE compensation accuracy It showed LSM could not increase TDE compensation accuracy further [28]. A modified RBF ANN-based TDE compensation model is established and its parameters are identified precisely It can estimate TDE more accurately and decouple Si-based materials’ temperature dependence effectively, and that increases MEMS-gyros’ stability and improves the environmental adaptability.
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