Technology For Elimination of MEMS Gyroscope Zero Offset under the Influence of Linear Acceleration and the Occurrence of Skewnesses in the Locations of Sensor Block Installation

2020 ◽  
Author(s):  
Aleksey Krylov
Keyword(s):  
Linear Acceleration ◽  
Mems Gyroscope ◽  
Zero Offset ◽  
Sensor Block

Spurious Signals in the Thermal MEMS Gyroscope

2012 ◽  
Author(s):  
Pooneh Shooshtari ◽  
Jamal Bahari ◽  
Kourosh Khosraviani ◽  
Albert Leung ◽  
John Jones
Keyword(s):  
Mathematical Model ◽  
Fluid Flow ◽  
Linear Acceleration ◽  
Temperature Sensors ◽  
Experimental Measurements ◽  
Micro Electro Mechanical Systems ◽  
Mems Gyroscope ◽  
Two Factors ◽  
Spurious Signals ◽  
Rotation Signal

The operational principle of a thermal MEMS (Micro Electro-Mechanical Systems) gyroscope was reported in Hilton Head 2010 [1]. In the current work we describe two factors that can produce a spurious rotation signal in gyroscopes of this type. These factors are, firstly, distortion or asymmetric placement of the heating elements or temperature sensors; secondly, the effects of linear acceleration and/or gravity on the fluid flow inside the device, and hence on the gyroscope output. In order to simulate the thermal gyro and the origin of these spurious signals, a mathematical model is built and developed through the COMSOL CFD package. The spurious signals predicted by this simulation are shown to correspond to experimental measurements. Alternative cavity shapes are investigated and simulated as a mean of suppressing the spurious signal.

Yaw/Heading Optimization by Drift Elimination on MEMS Gyroscope

2021 ◽  
pp. 112691
Author(s):  
Minh Long Hoang ◽  
Antonio Pietrosanto
Keyword(s):  
Mems Gyroscope

Head Impact Biomechanics in Youth Flag Football: A Prospective Cohort Study

2021 ◽  
pp. 036354652110266
Author(s):  
Landon B. Lempke ◽  
Rachel S. Johnson ◽  
Rachel K. Le ◽  
Melissa N. Anderson ◽  
Julianne D. Schmidt ◽  
...  
Keyword(s):  
Mixed Model ◽  
Linear Acceleration ◽  
Cross Sectional Study ◽  
Head Impact ◽  
Rotational Acceleration ◽  
Event Type ◽  
Level Of Evidence ◽  
Cross Sectional ◽  
Head Impact Biomechanics ◽  
Impact Biomechanics

Background: Youth flag football participation has rapidly grown and is a potentially safer alternative to tackle football. However, limited research has quantitatively assessed youth flag football head impact biomechanics. Purpose: To describe head impact biomechanics outcomes in youth flag football and explore factors associated with head impact magnitudes. Study Design: Cross-sectional study; Level of evidence, 3. Methods: We monitored 52 player-seasons among 48 male flag football players (mean ± SD; age, 9.4 ± 1.1 years; height, 138.6 ± 9.5 cm; mass, 34.7 ± 9.2 kg) across 3 seasons using head impact sensors during practices and games. Sensors recorded head impact frequencies, peak linear ( g) and rotational (rad/s2) acceleration, and estimated impact location. Impact rates (IRs) were calculated as 1 impact per 10 player-exposures; IR ratios (IRRs) were used to compare season, event type, and age group IRs; and 95% CIs were calculated for IRs and IRRs. Weekly and seasonal cumulative head impact frequencies and magnitudes were calculated. Mixed-model regression models examined the association between player characteristics, event type, and seasons and peak linear and rotational accelerations. Results: A total of 429 head impacts from 604 exposures occurred across the study period (IR, 7.10; 95% CI, 4.81-10.50). Weekly and seasonal cumulative median head impact frequencies were 1.00 (range, 0-2.63) and 7.50 (range, 0-21.00), respectively. The most frequent estimated head impact locations were the skull base (n = 96; 22.4%), top of the head (n = 74; 17.2%), and back of the head (n = 66; 15.4%). The combined event type IRs differed among the 3 seasons (IRR range, 1.45-2.68). Games produced greater IRs (IRR, 1.24; 95% CI, 1.01-1.53) and peak linear acceleration (mean difference, 5.69 g; P = .008) than did practices. Older players demonstrated greater combined event–type IRs (IRR, 1.46; 95% CI, 1.12-1.90) and increased head impact magnitudes than did younger players, with every 1-year age increase associated with a 3.78 g and 602.81-rad/s2 increase in peak linear and rotational acceleration magnitude, respectively ( P≤ .005). Conclusion: Head IRs and magnitudes varied across seasons, thus highlighting multiple season and cohort data are valuable when providing estimates. Head IRs were relatively low across seasons, while linear and rotational acceleration magnitudes were relatively high.

scholarly journals A Combined Method for MEMS Gyroscope Error Compensation Using a Long Short-Term Memory Network and Kalman Filter in Random Vibration Environments

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1181
Author(s):  
Chenhao Zhu ◽  
Sheng Cai ◽  
Yifan Yang ◽  
Wei Xu ◽  
Honghai Shen ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Standard Deviation ◽  
Error Compensation ◽  
Random Vibration ◽  
Short Term Memory ◽  
Combined Method ◽  
Short Term ◽  
Mems Gyroscope ◽  
Long Short Term Memory ◽  
Lstm Network

In applications such as carrier attitude control and mobile device navigation, a micro-electro-mechanical-system (MEMS) gyroscope will inevitably be affected by random vibration, which significantly affects the performance of the MEMS gyroscope. In order to solve the degradation of MEMS gyroscope performance in random vibration environments, in this paper, a combined method of a long short-term memory (LSTM) network and Kalman filter (KF) is proposed for error compensation, where Kalman filter parameters are iteratively optimized using the Kalman smoother and expectation-maximization (EM) algorithm. In order to verify the effectiveness of the proposed method, we performed a linear random vibration test to acquire MEMS gyroscope data. Subsequently, an analysis of the effects of input data step size and network topology on gyroscope error compensation performance is presented. Furthermore, the autoregressive moving average-Kalman filter (ARMA-KF) model, which is commonly used in gyroscope error compensation, was also combined with the LSTM network as a comparison method. The results show that, for the x-axis data, the proposed combined method reduces the standard deviation (STD) by 51.58% and 31.92% compared to the bidirectional LSTM (BiLSTM) network, and EM-KF method, respectively. For the z-axis data, the proposed combined method reduces the standard deviation by 29.19% and 12.75% compared to the BiLSTM network and EM-KF method, respectively. Furthermore, for x-axis data and z-axis data, the proposed combined method reduces the standard deviation by 46.54% and 22.30% compared to the BiLSTM-ARMA-KF method, respectively, and the output is smoother, proving the effectiveness of the proposed method.

scholarly journals Design Approach for Reducing Cross-Axis Sensitivity in a Single-Drive Multi-Axis MEMS Gyroscope

Micromachines ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 902
Author(s):  
Hussamud Din ◽  
Faisal Iqbal ◽  
Byeungleul Lee
Keyword(s):  
Microelectromechanical Systems ◽  
Reduction Rate ◽  
Design Technique ◽  
Matching Method ◽  
Mems Gyroscope ◽  
Mode Split ◽  
The Cross ◽  
The Individual ◽  
Cross Axis ◽  
Ratio Matching

In this paper, a new design technique is presented to estimate and reduce the cross-axis sensitivity (CAS) in a single-drive multi-axis microelectromechanical systems (MEMS) gyroscope. A simplified single-drive multi-axis MEMS gyroscope, based on a mode-split approach, was analyzed for cross-axis sensitivity using COMSOL Multiphysics. A design technique named the “ratio-matching method” of drive displacement amplitudes and sense frequency differences ratios was proposed to reduce the cross-axis sensitivity. Initially, the cross-axis sensitivities in the designed gyroscope for x and y-axis were calculated to be 0.482% and 0.120%, respectively, having an average CAS of 0.301%. Using the proposed ratio-matching method and design technique, the individual cross-axis sensitivities in the designed gyroscope for x and y-axis were reduced to 0.018% and 0.073%, respectively. While the average CAS was reduced to 0.045%, showing a reduction rate of 85.1%. Moreover, the proposed ratio-matching method for cross-axis sensitivity reduction was successfully validated through simulations by varying the coupling spring position and sense frequency difference variation analyses. Furthermore, the proposed methodology was verified experimentally using fabricated single-drive multi-axis gyroscope.

scholarly journals Development of a new method for assessing otolith function in mice using three-dimensional binocular analysis of the otolith-ocular reflex

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shotaro Harada ◽  
Takao Imai ◽  
Yasumitsu Takimoto ◽  
Yumi Ohta ◽  
Takashi Sato ◽  
...  
Keyword(s):  
Eye Movement ◽  
Three Dimensional ◽  
Vertical Component ◽  
Inertial Force ◽  
Linear Acceleration ◽  
The Body ◽  
Body Axis ◽  
Gravitational Acceleration ◽  
Ocular Reflex ◽  
Translational Movement

AbstractIn the interaural direction, translational linear acceleration is loaded during lateral translational movement and gravitational acceleration is loaded during lateral tilting movement. These two types of acceleration induce eye movements via two kinds of otolith-ocular reflexes to compensate for movement and maintain clear vision: horizontal eye movement during translational movement, and torsional eye movement (torsion) during tilting movement. Although the two types of acceleration cannot be discriminated, the two otolith-ocular reflexes can distinguish them effectively. In the current study, we tested whether lateral-eyed mice exhibit both of these otolith-ocular reflexes. In addition, we propose a new index for assessing the otolith-ocular reflex in mice. During lateral translational movement, mice did not show appropriate horizontal eye movement, but exhibited unnecessary vertical torsion-like eye movement that compensated for the angle between the body axis and gravito-inertial acceleration (GIA; i.e., the sum of gravity and inertial force due to movement) by interpreting GIA as gravity. Using the new index (amplitude of vertical component of eye movement)/(angle between body axis and GIA), the mouse otolith-ocular reflex can be assessed without determining whether the otolith-ocular reflex is induced during translational movement or during tilting movement.

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