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Fault Diagnosis of MEMS Lateral Comb Resonators Using Multiple-Model Adaptive Estimators

机译:基于多模型自适应估计器的MEMS横向梳状谐振器故障诊断

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In this brief a fault diagnostic unit is developed for microelectromechanical systems (MEMS) by means of multiple model adaptive estimation technique. Fault modeling tools such as contamination and reliability analysis of microelectromechanical layout enabled interpretation of microsystems behavior by evaluating their structural variations and modeling them in form of electric circuits. This technique cannot directly diagnose the faults during operation of microsystems. However, these fault-representing models can be used in multiple model adaptive estimation technique to form fault diagnosis units. Here, fault-representing systems are modeled by Kalman filters in real-time applications and are used to evaluate the fault in microsystems. MEMS lateral comb resonators are fabricated to experimentally demonstrate the fault diagnosis performance in multiple model adaptive estimation technique.
机译:在本文中,通过多模型自适应估计技术为微机电系统(MEMS)开发了故障诊断单元。故障建模工具,例如污染和微机电布局的可靠性分析,可以通过评估微系统的结构变化并以电路形式对它们进行建模,从而对微系统的行为进行解释。该技术不能直接诊断微系统运行期间的故障。但是,这些故障表示模型可以在多模型自适应估计技术中使用,以形成故障诊断单元。在这里,故障表示系统由实时应用中的卡尔曼滤波器建模,并用于评估微系统中的故障。制作了MEMS横向梳状谐振器,以实验证明多模型自适应估计技术中的故障诊断性能。

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