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FPGA implementation of a low-cost method for tracking the resonance frequency and the quality factor of MEMS sensors

机译:FpGa实现了一种低成本跟踪共振频率和mEms传感器质量的方法

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摘要

This paper reports the hardware implementation of a low-cost parameter estimation method (LIMBO) and describes its use for tracking the parameters of a resonant MEMS sensor. We show how this method can be used to identify the impulse response (IR) of a sensor with minimal A/D-D/A requirements. Based on this IR, we develop digital estimators capable of extracting the resonance frequency and the quality factor. The full electronic architecture is simulated on a mixed-signal environment and implemented on FPGA-based digital hardware. For a specifically emulated sensor, results show that the resonance frequency can be identified and tracked from 3kHz up to 12kHz with a Normalized Square Error (NSE) of 1.38E-1. The quality factor is linearized with a correlation coefficient of 0.986 between Q=1 to Q=60. Those results can be easily scaled to any frequency range by adapting the sampling frequency.
机译:本文报告了低成本参数估计方法(LIMBO)的硬件实现,并描述了用于跟踪谐振MEMS传感器的参数的用途。我们展示了如何使用该方法来识别具有最小A / D-D / A要求的传感器的脉冲响应(IR)。基于此IR,我们开发能够提取谐振频率和质量因数的数字估计器。全电子架构在混合信号环境上模拟,并在基于FPGA的数字硬件上实现。对于专门的仿真传感器,结果表明,可以使用1.38e-1的标准化方误差(nse)从3khz识别和跟踪共振频率。质量因子在Q = 1至Q = 60之间的相关系数为0.986。通过调整采样频率,这些结果可以很容易地缩放到任何频率范围。

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