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Design and Development of Ultralow-Power MEMS Lead-Free Piezoelectric Accelerometer Digital System for Unmanned Aerial Vehicle Motor Monitoring

加速度计 电子工程 运算放大器 微电子机械系统 有效位数 压电加速度计 电气工程 放大器 工程类 计算机科学 CMOS芯片 压电 压电传感器 物理 光电子学 操作系统
作者
Cheng-Ying Li,Soon-Jyh Chang,Ro‐Min Weng,Sin-Yu Ciou,Zehui Chen,Po-Yu Hsiao,Yen-Hsiang Huang,T.Y. Wang,Yi‐Chia Lee,Yun‐Hui Liu,Cheng‐Che Tsai,Sheng‐Yuan Chu
出处
期刊:IEEE Sensors Journal [IEEE Sensors Council]
卷期号:23 (16): 18599-18608 被引量:1
标识
DOI:10.1109/jsen.2023.3289433
摘要

In this article, an ultralow-power microelectromechanical system (MEMS) lead-free piezoelectric accelerometer digital system is developed. This proposed system is mainly composed of a MEMS lead-free piezoelectric accelerometer and a readout circuit with successive approximation register (SAR) analog-to-digital converter (ADC). In this work, ANSYS software is used to design the structure, and LZO (ZnO: 3 mol% Li) piezoelectric films are deposited by radio frequency (RF) sputtering method, and LZO-based MEMS lead-free piezoelectric accelerometers are developed with an effective bandwidth of about 600 Hz in the 3-dB range through the MEMS process. The proposed readout circuit achieves high linearity and ultralow power consumption by optimizing each operational amplifier (OPAMP) according to the linearity requirement of the whole system. The differential architecture is adopted to deal with the sensed signal for the purpose of reducing the common-mode noise. A proof-of-concept chip is implemented in a 0.18- $\mu \text{m}$ CMOS process. At 1.8-V supply voltage and 100-kS/s sampling rate, the ADC achieves a signal-to-noise-and-distortion ratio (SNDR) of 58.92 dB and a corresponding effective number of bits (ENOB) of 9.5 bits for an input at Nyquist frequency. The power consumption of the ADC is $2.18 \mu \text{W}$ , resulting a figure-of-merit (FoM) of 30.1 fJ/conversion step. Combining with the piezoelectric accelerometer, the accelerometer system can achieve 600-Hz bandwidth with a 142-mV/ ${g}$ sensitivity and the linearity is 0.9998. Finally, this system is applied to the unmanned aerial vehicle to monitor the motor health status and successfully judge whether the motor of the unmanned aerial vehicle is abnormal.
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