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Modification of MTEA-Based Temperature Drift Error Compensation Model for MEMS-Gyros

机译：基于MTEA的MEMS-陀螺仪温度漂移误差补偿模型的修正

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摘要

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.
机译：常规的温度漂移误差（TDE）补偿模型无法解耦硅基材料的温度依赖性，因为尚未全面获得温度相关量（TCQ），并且微机电系统陀螺仪（MEMS-gyros'）的环境适应性是减少了各种复杂情况。该研究提出了基于微结构热效应分析（MTEA）的MEMS陀螺仪TDE补偿模型修正。首先，在具有热膨胀效应的微观结构中研究了硅基材料的温度依赖性，并提取了确定结构变形的TCQ来修改常规模型，包括温度变化及其平方。其次，通过分析MEMS陀螺仪与热室之间的导热过程，形成一种精确的TDE测试方法，并设计并进行了温度实验。第三，基于根基函数人工神经网络（RBF ANN）识别修改后的模型的参数，并评估其性能。最后，比较了常规模型和改进模型的性能。实验结果表明，MEMS-陀螺仪的偏置稳定性高达常规模型的10％，改进后的硅基材料对温度的依赖性更好地解耦，提高了MEMS-陀螺仪的环境适应性，扩大了其应用范围。各种复杂的条件。

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