A high precision MEMS based capacitive accelerometer for seismic measurements

Utz, Alexander; Walk, Christian; Stanitzki, Alexander; Mokhtari, Mir; Kraft, Michaël; Kokozinski, Rainer

doi:10.1109/icsens.2017.8233981

Cited by 6 publications

(7 citation statements)

References 6 publications

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“…In most studies [ 5 , 6 , 7 , 8 , 9 , 12 , 13 , 15 , 16 , 17 , 24 , 25 , 26 , 27 , 28 ], finger flexibility is ignored to assume the sensing element of the seismic-grade MEMS accelerometer as a single-degree-of-freedom (SDOF) mass–damper–spring system. However, this conventional approach is unable to capture the effects of high-order mechanical resonances.…”

Section: Mdof-em Model Of the Sensing Elementmentioning

confidence: 99%

“…If ignoring the flexibility of the fingers, i.e., the normalized finger displacements

are assumed to be zero, the MDOF-EM model given in Equation (19) degrades into the SDOF-EM model that is widely adopted in current studies [ 5 , 6 , 7 , 8 , 9 , 12 , 13 , 15 , 16 , 17 , 24 , 25 , 26 , 27 , 28 ].

…”

Section: Mdof-em Model Of the Sensing Elementmentioning

confidence: 99%

“…Brownian noise can be lowered by improving the weight of the proof mass and the quality factor (Q) [ 7 , 8 ]. Thus, the sensing element of seismic-grade MEMS accelerometers is usually packaged in a vacuum to ensure high Q [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

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Multiple-Degree-of-Freedom Modeling and Simulation for Seismic-Grade Sigma–Delta MEMS Capacitive Accelerometers

Wang

Zhang

2023

Sensors

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The high-order mechanical resonances of the sensing element in a high-vacuum environment can significantly degrade the noise and distortion performance of seismic-grade sigma–delta MEMS capacitive accelerometers. However, the current modeling approach is unable to evaluate the effects of high-order mechanical resonances. This study proposes a novel multiple-degree-of-freedom (MDOF) model to evaluate the noise and distortion induced by high-order mechanical resonances. Firstly, the MDOF dynamic equations of the sensing element are derived using the principle of modal superposition and Lagrange’s equations. Secondly, a fifth-order electromechanical sigma–delta system of the MEMS accelerometer is established in Simulink based on the dynamic equations of the sensing element. Then, the mechanism through which the high-order mechanical resonances degrade the noise and distortion performances is discovered by analyzing the simulated result. Finally, a noise and distortion suppression method is proposed based on the appropriate improvement in high-order natural frequency. The results show that the low-frequency noise drastically decreases from about −120.5 dB to −175.3 dB after the high-order natural frequency increases from about 130 kHz to 455 kHz. The harmonic distortion also reduces significantly.

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Section: Mdof-em Model Of the Sensing Elementmentioning

confidence: 99%

“…If ignoring the flexibility of the fingers, i.e., the normalized finger displacements

…”

Section: Mdof-em Model Of the Sensing Elementmentioning

confidence: 99%

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Multiple-Degree-of-Freedom Modeling and Simulation for Seismic-Grade Sigma–Delta MEMS Capacitive Accelerometers

Wang

Zhang

2023

Sensors

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“…MEMS-based acceleration sensors are widely used in many applications [1][2][3][4][5]. Generally, we can distinguish the following sensors: one-axis and three-axis accelerometers according to their design [6,7].…”

Section: Introductionmentioning

confidence: 99%

Thermal Performance of a Capacitive Comb-Drive MEMS Accelerometer: Measurements vs. Simulation

et al. 2021

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In this work, we analysed the difference between the measurement and simulation results of thermal drift of a custom designed capacitive MEMS accelerometer. It was manufactured in X-FAB XMB10 technology together with a dedicated readout circuit in X-FAB XP018 technology. It turned out that the temperature sensitivity of the sensor’s output is nonlinear and particularly strong in the negative Celsius temperature range. It was found that the temperature drift is mainly caused by the MEMS sensor and the influence of the readout circuit is minimal. Moreover, the measurements showed that this temperature dependence is the same regardless of applied acceleration. Simulation of the accelerometer’s model allowed us to estimate the contribution of post-manufacturing mismatch on the thermal drift; for our sensor, the mismatch-induced drift accounted for about 6% of total thermal drift. It is argued that the remaining 94% of the drift could be a result of the presence of residual stress in the structure after fabrication.

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“…These advantages include higher sensitivity, rapid detection, and the integration of electrical readout circuits and sensing electrodes on a single chip. In spite of microelectromechanical systems (MEMS)-based capacitive sensors such as accelerometers [ 1 , 2 ], position sensors [ 3 , 4 ], pressure sensors [ 5 , 6 , 7 , 8 ], and moisture sensors [ 9 ], a growing body of literature has studied capacitive sensors for Laboratory on a Chip (LoC) applications. These applications include DNA hybridization detection [ 10 ], protein interactions quantification [ 11 ], cellular monitoring [ 12 , 13 , 14 ], bio-particle detection [ 15 ], microRNA detection [ 16 ], organic solvent monitoring [ 17 ], sensing of droplet parameters [ 18 ], and bacteria detection [ 19 , 20 ].…”

Section: Introductionmentioning

confidence: 99%

Toward High Throughput Core-CBCM CMOS Capacitive Sensors for Life Science Applications: A Novel Current-Mode for High Dynamic Range Circuitry

Forouhi

Dehghani

Ghafar-Zadeh

2018

Sensors

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This paper proposes a novel charge-based Complementary Metal Oxide Semiconductor (CMOS) capacitive sensor for life science applications. Charge-based capacitance measurement (CBCM) has significantly attracted the attention of researchers for the design and implementation of high-precision CMOS capacitive biosensors. A conventional core-CBCM capacitive sensor consists of a capacitance-to-voltage converter (CVC), followed by a voltage-to-digital converter. In spite of their high accuracy and low complexity, their input dynamic range (IDR) limits the advantages of core-CBCM capacitive sensors for most biological applications, including cellular monitoring. In this paper, after a brief review of core-CBCM capacitive sensors, we address this challenge by proposing a new current-mode core-CBCM design. In this design, we combine CBCM and current-controlled oscillator (CCO) structures to improve the IDR of the capacitive readout circuit. Using a 0.18 μm CMOS process, we demonstrate and discuss the Cadence simulation results to demonstrate the high performance of the proposed circuitry. Based on these results, the proposed circuit offers an IDR ranging from 873 aF to 70 fF with a resolution of about 10 aF. This CMOS capacitive sensor with such a wide IDR can be employed for monitoring cellular and molecular activities that are suitable for biological research and clinical purposes.

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A high precision MEMS based capacitive accelerometer for seismic measurements

Cited by 6 publications

References 6 publications

Multiple-Degree-of-Freedom Modeling and Simulation for Seismic-Grade Sigma–Delta MEMS Capacitive Accelerometers

Multiple-Degree-of-Freedom Modeling and Simulation for Seismic-Grade Sigma–Delta MEMS Capacitive Accelerometers

Thermal Performance of a Capacitive Comb-Drive MEMS Accelerometer: Measurements vs. Simulation

Toward High Throughput Core-CBCM CMOS Capacitive Sensors for Life Science Applications: A Novel Current-Mode for High Dynamic Range Circuitry

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