Control and estimation with threshold sensing for Inertial Measurement Unit calibration using a piezoelectric microstage

Edamana, Biju; Slavin, Daniel; Aktakka, Ethem Erkan; Oldham, Kenn R.

doi:10.1109/acc.2014.6859359

Cited by 8 publications

(6 citation statements)

References 13 publications

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“…Through the simulation, we can acknowledge that utilizing adaptive threshold extraction method based on wavelet entropy in processing and filtering weak signals, no matter in high SNR or low SNR, the four parameters are superior to the soft threshold extraction, and the lower SNR, the more obvious advantage the wavelet entropy of adaptive threshold extraction methods perform. Table 3 Data contrast between soft-threshold method and wavelet entropy methods when SNR=-9dB de-noise method soft threshold de-noising Wavelet entropy de-noising SNR/dB * 0.2307 SNRG/dB * 9.2307 mean of residual errorsε/mV 0.0011 0.0011 mean square errorσ/mV 2 1.0902 0.6912…”

Section: (2) Snr=-5dbmentioning

confidence: 99%

“…Signals in measurement & control system of microstage systems usually suffer the electromagnetic interference from the noise in the internal of system and random disturbance from the external environment. All of these types of noise can reduce the positioning accuracy of microstage system [2]. Since the signal-to-noise ratio (SNR) of the weak signal is less than 0 dB in most cases, absolute amplitude value of the measured useful signal is so small that it is easy to be drown in the noise.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Research about Weak Signal Processing of Microstage Based on Wavelet Entropy

Cao¹,

Lu²,

Zhang³

et al. 2015

Proceedings of the 2015 International Conference on Electrical, Computer Engineering and Electronics

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This paper deals with the research on conditioning and filtering scheme of weak signals for the micro-positioning-stage and its measurement & control system. Through the analysis of the general filtering scheme of the weak signals, and the combination with the performance index of the system, this paper filters the noises utilizing the weak signal adaptive threshold extraction method based on wavelet entropy. This paper carried out comparable simulation and experimental tests with the proposed threshold method. The test results show that the wavelet entropy based threshold extraction method can obtain higher SNR and SNRG.

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Section: (2) Snr=-5dbmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Research about Weak Signal Processing of Microstage Based on Wavelet Entropy

Cao¹,

Lu²,

Zhang³

et al. 2015

Proceedings of the 2015 International Conference on Electrical, Computer Engineering and Electronics

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“…A multi-axis vibratory platform designed by a team at the University of Michigan for in situ self-calibration of general MEMS inertial sensors [ 12 , 13 ], which can achieve 150°/s angular rate and 0.3 g (1 g = 9.8 m/s 2 ) linear acceleration. It is integrated with the commercial Invensense MPU-6500 (IMU) and is expected to provide the scale-factor calibration with estimation error <20 ppm, yet the capacitive position sensor for platform motion detection has temperature drift [ 14 ] and dielectric polarization effect [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

Impacts of Residual Stress on Micro Vibratory Platform Used for Inertial Sensor Calibration

Hao

Peng

et al. 2020

Sensors

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A micro vibratory platform driven by converse piezoelectric effects is a promising in-situ recalibration platform to eliminate the influence of bias and scale factor drift caused by long-term storage of micro-electro–mechanical system (MEMS) inertial sensors. The calibration accuracy is critically determined by the stable and repeatable vibration of platform, and it is unavoidably impacted by the residual stress of micro structures and lead zirconate titanate (PZT) hysteresis. The abnormal phenomenon of the observed displacement response in experiments was investigated analytically using the stiffness model of beams and hysteresis model of piezoelectric material. Rather than the hysteresis, the initial deflection formed by the residual stress of the beam was identified as the main cause of the response error around the zero position. This conclusion provides guidelines to improve the performance and control of micro vibratory platforms.

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“…The platform consists of a 3-DOF micromotion stage that can provide piezoelectric actuation for Z-translation and X/Y-tilting reference stimuli with a small off-axis motion compared to the preferred direction of actuation. The following research works are mainly focused on the in-situ calibration method for the gyroscope as well as the fabrication of larger micro vibrators [ 9 , 10 , 11 , 12 , 13 , 14 ]. Further, the transient linear acceleration and angular velocity output of those vibrators grow continuously up to 0.3 g [ 15 ] and 280°/s [ 10 ], respectively.…”

Section: Introductionmentioning

confidence: 99%

“…The system architecture is simple without the need for an additional sensor section, but the detection accuracy and repeatability are not high. Another method of motion detection for MEMS-IMU is based on capacitive sensing, which provides a threshold point with very high precision in the case of skillfully imbedding the capacitor plate electrodes at the bottom side of the vibratory stage and substrate [ 11 , 14 ]. When the detected current changes from positive to negative, the corresponding displacement is considered to be accurate and a threshold signal is given.…”

Section: Introductionmentioning

confidence: 99%

High Dynamic Micro Vibrator with Integrated Optical Displacement Detector for In-Situ Self-Calibration of MEMS Inertial Sensors

Yang

Gong

et al. 2018

Sensors

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The scale factor drifts and other long-term instability drifts of Micro-Electro-Mechanical SystemMEMS) inertial sensors are the main contributors of the position and orientation errors in high dynamic environments. In this paper, a novel high dynamic micro vibrator, which could provide high acceleration and high angular rate rotation with integrated optical displacement detector, is proposed. Commercial MEMS inertial sensors, including 3-axis accelerometer and 6-axis inertial measurement unit which is about 3 mm * 3 mm * 1 mm with 19 mg, could be bonded on the vibration platform of the micro vibrator to perform in-situ during the self-calibration procedure. The high dynamic micro vibrator is fabricated by a fully-integrated MEMS process, including lead zirconate titanate (PZT) film deposition, PZT and electrodes patterning, and structural ion etching. The optical displacement detector, using vertical-cavity surface-emitting laser (VCSEL) and photoelectric diodes (PD), is integrated on the top of the package to measure the 6-DOF vibrating displacement with the detecting resolution of 150 nm in the range of 500 μm. The maximum out-of-plane acceleration of the z-axis vibrating platform loaded with commercial 3-axis accelerometer (H3LIS331DL) achieves above 16 g and the maximum angular velocity achieves above 720°/s when the driving voltage is ±6 V.

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Control and estimation with threshold sensing for Inertial Measurement Unit calibration using a piezoelectric microstage

Cited by 8 publications

References 13 publications

Research about Weak Signal Processing of Microstage Based on Wavelet Entropy

Research about Weak Signal Processing of Microstage Based on Wavelet Entropy

Impacts of Residual Stress on Micro Vibratory Platform Used for Inertial Sensor Calibration

High Dynamic Micro Vibrator with Integrated Optical Displacement Detector for In-Situ Self-Calibration of MEMS Inertial Sensors

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