This MS thesis studies how to resolve the feed-through parasitic capacitance always present in MEMS vibratory capacitive sensors. MEMS capacitive sensors have been integrated into various applications due to their compact size, low power consumption, and compatibility with IC components. However, feed-through parasitic capacitance is a major issue that directly impacts the actual sensor reading, especially for miniaturized sensors. The unintended capacitance readings can result in measurement inaccuracies and degrade the signal-to-noise ratio (SNR). Electromechanical Amplitude Modulation (EAM) technique is used in this thesis to address the issue caused by feed-through parasitic capacitance within the sensors.
EAM technique involves modulating a carrier signal and an AC driving signal to the sensor. A high-frequency carrier signal is applied to the sensor, modulating the sensor outputs to a higher-frequency region as sidebands of the carrier signal. This approach isolates the motional signal of the sensor from parasitic capacitance and background noise. The motional sensor output can be then reconstructed through demodulation and filtering. The modeling results were confirmed experimentally to mitigate the parasitic capacitance from the true sensor output using the EAM technique.
Two MEMS vibratory capacitance sensors were the focus of this thesis for experimentally validation of the EAM technique: an Epi-Seal Toroidal Ring Gyroscope (TRG) and a Frequency-Modulated (FM) Accelerometer. The experimental setup consists of trans-impedance amplifiers, a control feedback loop with a Phase-Locked Loop (PLL), and Automatic Gain Control (AGC) to maintain the sensor in self-resonance with consistent amplitude and phase. Key performance metrics of the MEMS sensors were extracted, including the resonance frequency, quality factor, sensitivity, and noise parameters from Allan deviation analysis. The results of both sensors confirmed that the EAM technique can mitigate and increase the SNR of the sensor, improving the performance and sensitivity of the MEMS vibratory capacitive sensors.