scholarly journals A Filtering Algorithm of MEMS Gyroscope to Resist Acoustic Interference

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7352
Author(s):  
Yufei Sun ◽  
Peng Guo ◽  
Lihui Feng ◽  
Chaoyang Xing ◽  
Junjie Wu
Keyword(s):  
Angular Velocity ◽  
Single Channel ◽  
Noise Signal ◽  
Interference Signal ◽  
Sound Waves ◽  
Velocity Signal ◽  
Mems Gyroscope ◽  
Filtering Algorithm ◽  
Acoustic Interference ◽  
The Impact

To reduce the impact of acoustic interference in a microelectromechanical system (MEMS) gyroscope and to improve the reliability of output data, a filtering algorithm based on orthogonal demodulation is proposed. According to the working principle and failure mechanism of a MEMS gyroscope, the sound and angular velocity frequencies are not identical, which lead to a different frequency signal output of the original single-channel demodulation scheme. Therefore, a Q channel demodulation filtering process was added to the origin single-channel demodulation scheme. For the Q channel demodulated signal, a Hilbert transform was used to compensate for the 90 degree phase shift. The IQ dual-channel difference can remove the acoustic interference signal. The simulation results indicate that the scheme can effectively suppress the acoustic interference signal and it can eliminate more than 95% of the impact of sound waves. We assembled the acoustic interference experimental platform, collected the driving and sensing data, and verified the denoising performance with our algorithm, which eliminated more than 70% of the noise signal. The simulation and experimental results demonstrate that the scheme can eliminate acoustic interference signal without destroying angular velocity signal.

scholarly journals Research on Filtering Algorithm of MEMS Gyroscope Based on Information Fusion

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3552
Author(s):  
Hui Guo ◽  
Huajie Hong
Keyword(s):  
Angular Velocity ◽  
Information Fusion ◽  
Electromagnetic Interference ◽  
Inertial Sensor ◽  
Random Noise ◽  
Accurate Estimation ◽  
Velocity Signal ◽  
Mems Gyroscope ◽  
The Stability ◽  
Filtering Function

As an important inertial sensor, the gyroscope is mainly used to measure angular velocity in inertial space. However, due to the influence of semiconductor thermal noise and electromagnetic interference, the output of the gyroscope has a certain random noise and drift, which affects the accuracy of the detected angular velocity signal, thus interfering with the accuracy of the stability of the whole system. In order to reduce the noise and compensate for the drift of the MEMS (Micro Electromechanical System) gyroscope during usage, this paper proposes a Kalman filtering method based on information fusion, which uses the MEMS gyroscope and line accelerometer signals to implement the filtering function under the Kalman algorithm. The experimental results show that compared with the commonly used filtering methods, this method allows significant reduction of the noise of the gyroscope signal and accurate estimation of the drift of the gyroscope signal, and thus improves the control performance of the system and the stability accuracy.

Simulation of athlete gait recognition based on spectral features and machine learning

2020 ◽  
pp. 1-12
Author(s):  
Linuo Wang
Keyword(s):  
Machine Learning ◽  
Angular Velocity ◽  
Gait Recognition ◽  
Spectral Feature ◽  
Velocity Signal ◽  
Comparison Results ◽  
Computer Vision Technology ◽  
Feature Technology ◽  
Leg Movement ◽  
Recognition Efficiency

The current technology related to athlete gait recognition has shortcomings such as complicated equipment and high cost, and there are also certain problems in recognition accuracy and recognition efficiency. In order to improve the efficiency of athletes’ gait recognition, this paper studies the different recognition technologies of athletes based on machine learning and spectral feature technology and applies computer vision technology to sports. Moreover, according to the calf angular velocity signal, the occurrence of leg movement is detected in real time, and the gait cycle is accurately divided to reduce the influence of the signal unrelated to the behavior on the recognition process. In addition, this study proposes a gait behavior recognition method based on event-driven strategies. This method uses a gyroscope as the main sensor and uses a wearable sensor node to collect the angular velocity signals of the legs and waist. In addition, this study analyzes the performance of the algorithm proposed by this paper through experimental research. The comparison results show that the method proposed by this paper has improved the number of recognition action types and accuracy and has certain advantages from the perspective of computation and scalability.

scholarly journals Time-jerk optimal trajectory planning of hydraulic robotic excavator

2021 ◽  
Vol 13 (7) ◽  
pp. 168781402110346
Author(s):  
Yunyue Zhang ◽  
Zhiyi Sun ◽  
Qianlai Sun ◽  
Yin Wang ◽  
Xiaosong Li ◽  
...  
Keyword(s):  
Angular Velocity ◽  
Trajectory Planning ◽  
Optimal Trajectory ◽  
High Efficiency ◽  
Optimal Solution ◽  
Optimal Time ◽  
Target Point ◽  
Robotic Excavator ◽  
The Impact ◽  
Optimal Trajectory Planning

Due to the fact that intelligent algorithms such as Particle Swarm Optimization (PSO) and Differential Evolution (DE) are susceptible to local optima and the efficiency of solving an optimal solution is low when solving the optimal trajectory, this paper uses the Sequential Quadratic Programming (SQP) algorithm for the optimal trajectory planning of a hydraulic robotic excavator. To achieve high efficiency and stationarity during the operation of the hydraulic robotic excavator, the trade-off between the time and jerk is considered. Cubic splines were used to interpolate in joint space, and the optimal time-jerk trajectory was obtained using the SQP with joint angular velocity, angular acceleration, and jerk as constraints. The optimal angle curves of each joint were obtained, and the optimal time-jerk trajectory planning of the excavator was realized. Experimental results show that the SQP method under the same weight is more efficient in solving the optimal solution and the optimal excavating trajectory is smoother, and each joint can reach the target point with smaller angular velocity, and acceleration change, which avoids the impact of each joint during operation and conserves working time. Finally, the excavator autonomous operation becomes more stable and efficient.

High Performance MEMS Thermal Gyroscope

2012 ◽  
Author(s):  
Nilgoon Zarei ◽  
Albert M. Leung ◽  
John D. Jones
Keyword(s):  
External Force ◽  
High Performance ◽  
Gas Flow ◽  
Element Model ◽  
Minimal Impact ◽  
Mems Gyroscope ◽  
Force Finding ◽  
Dimensional Finite Element ◽  
To Come ◽  
The Impact

This paper reports modeling a new design of Thermal MEMS gyroscope through the use of the Comsol Multiphysics software package. Being very small and having no movable parts have made thermal MEMS gyroscope very practical. Previously designed Thermal MEMS gyroscope shows some limitation such as being vulnerable to gravity force. Finding a technique to increase the range of thermal MEMS gyroscope reliability motivated us to come up with a new design that we will refer to as the ‘Forced Convection MEMS gyroscope’. A two-dimensional finite-element model of the device has been developed to investigate its performance. An external force has been introduced to the system to create a higher-velocity hot gas stream that will be deviated more in response to rotation. The external force should be great enough that convection currents resulting from gravity or acceleration will have minimal impact on the gyroscope sensitivity. A heating element can still be used, but its primary purpose is now to warm the flowing gas so that it can be detected by the sensors. In this paper we will also show that, in order to completely eliminate the impact of gravity and increase the sensitivity of the gyroscope, it is possible to eliminate the heaters entirely and instead use heated sensors to detect gas currents. In other words, the sensors are working as hot-wire anemometers. Our simulations suggest that this design variant results in higher sensitivity. We have also carried out optimization studies to identify the best location for the heaters and sensors. A prototype of this device has been fabricated based on MEMS techniques, and an external pump is used to produce an oscillating gas flow within the device.

scholarly journals Hydrodynamic Ram Effect Caused by Debris Hypervelocity Impact on Satellite Tank

2019 ◽  
Vol 9 (20) ◽  
pp. 4200 ◽  
Author(s):  
Beilei Zhao ◽  
Jiguang Zhao ◽  
Cunyan Cui ◽  
Yongsheng Duan
Keyword(s):  
Shock Wave ◽  
Angular Velocity ◽  
Hypervelocity Impact ◽  
Filling Ratio ◽  
Maximum Diameter ◽  
Residual Velocity ◽  
Hydrodynamic Ram ◽  
Ram Effect ◽  
The Impact ◽  
Bulge Height

To study the hydrodynamic ram effect caused by the debris hypervelocity impact on the satellite tank, a numerical simulation of the spherical debris impacting the satellite tank at the velocity of 7000 m/s was carried out based on ANSYS/LS-DYNA software. The attenuation law of debris velocity, the propagation process of the shock wave and the deformation of the tank walls were investigated. The influences of the liquid-filling ratio, the magnitude, and direction of angular velocity on the hydrodynamic ram effect were analyzed. Results show that the debris velocity decreased rapidly and the residual velocity was 263 m/s when the debris passed through the tank. The shock wave was hemispherical, and the pressure of shock wave was the smallest at the element with an angle of 90° to the impact line. The maximum diameter of the front perforation was larger than that of the back perforation and the bulge height on the front wall was smaller than that on the back wall. With the decrease of the liquid-filling ratio, the diameter of the perforations and bulge height decreased. When the debris impacted the satellite tank with the angular velocity in the x direction, the debris trajectory did not deflect. When the debris impacted the satellite tank with the angular velocities in the y and z direction, the debris trajectory deflected to the negative direction of the z axis and y axis, respectively. The magnitude of the angular velocity affects the residual velocity of debris and the diameter of perforations.

scholarly journals Analysis of Brand Visual Design Based on Collaborative Filtering Algorithm

2022 ◽  
Vol 2022 ◽  
pp. 1-8
Author(s):  
Gao Chaomeng ◽  
Wang Yonggang
Keyword(s):  
Collaborative Filtering ◽  
Visual Communication ◽  
Visual Design ◽  
Design System ◽  
Original Algorithm ◽  
Filtering Algorithm ◽  
Visual Communication Design ◽  
Communication Design ◽  
Collaborative Filtering Algorithm ◽  
The Impact

With the continuous development of China’s social economy, the competitiveness of brand market is gradually increasing. In order to improve their own level in brand building, major enterprises gradually explore and study visual communication design. Brand visual design has also received more and more attention. Building a complete and rich visual design system can improve the brand level and attract users to consume. Based on the abovementioned situation, this paper proposes to use collaborative filtering algorithm to analyze and study brand visual design. Firstly, a solution is proposed to solve the problem of low accuracy of general recommendation algorithm in brand goods. Collaborative filtering algorithm is used to analyze the visual communication design process of enterprise brand. Research on personalized image design according to consumers’ trust and recognition of brand design is conducted. In traditional craft brand visual design, we mainly study the impact of image design on consumer behavior. The brand loyalty model is used to predict and analyze the visual design effect. Also, the user’s evaluation coefficient is taken as the expression of brand visual design recognition. Finally, the collaborative filtering algorithm is optimized to improve the consumer similarity based on the original algorithm. The results show that the brand visual design using collaborative filtering algorithm can help enterprises obtain greater benefits in their own brand construction. It provides effective data help in the development of traditional craft brands.

scholarly journals Research on Novel Denoising Method of Variational Mode Decomposition in MEMS Gyroscope

2021 ◽  
Vol 21 (1) ◽  
pp. 19-24
Author(s):  
Xiaolei Wang ◽  
Huiliang Cao ◽  
Yuzhao Jiao ◽  
Taishan Lou ◽  
Guoqiang Ding ◽  
...  
Keyword(s):  
Resonant Frequency ◽  
Reduction Method ◽  
Noise Signal ◽  
Sampling Frequency ◽  
Variational Mode Decomposition ◽  
Denoising Method ◽  
Mems Gyroscope ◽  
Frequency Level ◽  
Mode Decomposition ◽  
Four Levels

Abstract The noise signal in the gyroscope is divided into four levels: sampling frequency level, device bandwidth frequency level, resonant frequency level, and carrier frequency level. In this paper, the signal in the dual-mass MEMS gyroscope is analyzed. Based on the variational mode decomposition (VMD) algorithm, a novel dual-mass MEMS gyroscope noise reduction method is proposed. The VMD method with different four-level center frequencies is used to process the original output signal of the MEMS gyroscope, and the results are analyzed by the Allan analysis of variance, which shows that the ARW of the gyroscope is increased from 1.998*10−1°/√h to 1.552*10−4°/√h, BS increased from 2.5261°/h to 0.0093°/h.

scholarly journals SPATIOLTEMPORAL MODELING THE IMPACT OF SURFACE CHARACTERISTICS VARIATIONS ON LAND SURFACE TEMPERATURE VARIATIONS: A CASE STUDY OF SAMALGHAN VALLY

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 401-405
Author(s):  
M. K. Firozjaei ◽  
M. Makki ◽  
J. Lentschke ◽  
M. Kiavarz ◽  
S. K. Alavipanah
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Single Channel ◽  
Incident Angle ◽  
Surface Characteristics ◽  
Slope Aspect ◽  
Biophysical Parameters ◽  
The Impact

Abstract. Spatiotemporal mapping and modeling of Land Surface Temperature (LST) variations and characterization of parameters affecting these variations are of great importance in various environmental studies. The aim of this study is a spatiotemporal modeling the impact of surface characteristics variations on LST variations for the studied area in Samalghan Valley. For this purpose, a set of satellite imagery and meteorological data measured at the synoptic station during 1988–2018, were used. First, single-channel algorithm, Tasseled Cap Transformation (TCT) and Biophysical Composition Index (BCI) were employed to estimate LST and surface biophysical parameters including brightness, greenness and wetness and BCI. Also, spatial modeling was used to modeling of terrain parameters including slope, aspect and local incident angle based on DEM. Finally, the principal component analysis (PCA) and the Partial Least Squares Regression (PLSR) were used to modeling and investigate the impact of surface characteristics variations on LST variations. The results indicated that surface characteristics vary significantly for case study in spatial and temporal dimensions. The correlation coefficient between the PC1 of LST and PC1s of brightness, greenness, wetness, BCI, DEM, and solar local incident angle were 0.65, −0.67, −0.56, 0.72, −0.43 and 0.53, respectively. Furthermore, the coefficient coefficient and RMSE between the observed LST variation and modelled LST variation based on PC1s of brightness, greenness, wetness, BCI, DEM, and local incident angle were 0.83 and 0.14, respectively. The results of study indicated the LST variation is a function of s terrain and surface biophysical parameters variations.

Impact Damage Detection in GFRP Laminates through Ultrasonic Imaging

2012 ◽  
Vol 585 ◽  
pp. 337-341 ◽  
Author(s):  
H. Rama Murthy Naik ◽  
J. Jerald ◽  
N. Rajesh Mathivanan
Keyword(s):  
Impact Energy ◽  
Ultrasonic Testing ◽  
Energy Levels ◽  
Low Velocity Impact ◽  
Image Processing Technique ◽  
Sound Waves ◽  
Low Velocity ◽  
Immersion Method ◽  
Pulse Echo ◽  
The Impact

Composite materials are increasingly used in aerospace, naval and automotive vehicles due to their high specific strength and stiffness. In the area of Non destructive testing, ultrasonic C-scans are used frequently to detect defects in composite components caused during fabrication and damage resulting from service conditions. Ultrasonic testing uses transmission of high frequency sound waves into a material to detect imperfections or to locate changes in material properties. The most commonly used ultrasonic testing technique is pulse echo and through transmission wherein sound is introduced into a test object and reflections (echoes) are returned to a receiver from internal imperfections. Under low-velocity impact loading delaminating is observed to be a major failure mode. This report presents the use of above two techniques to detect the damage in glass fiber reinforced plastic (GFRP) laminates. Pulse echo is used to locate the exact position of damage and through transmission is used to know the magnitude of damage in composite. This paper work will be carried out on two different thicknesses and at impact energy levels varying from 7 to 53J. The ensuring delamination damage will be determined by ultrasonic C-scans using the pulse-echo immersion method for through transmission. Delamination areas were quantified accurately by processing the raw image data using a digital image processing technique. Based on the data obtained, correlation will be established between the delamination area and the impact energy.

Separation Enhancement of Power Line Noise from Human ECG Signal Based on Stone Technique

2019 ◽  
Vol 40 ◽  
pp. 71-78 ◽  
Author(s):  
Ahmed Kareem Abdullah ◽  
Ahmed Ghanim Wadday ◽  
Ali A. Abdullah
Keyword(s):  
Disease Diagnosis ◽  
Noise Signal ◽  
Power Line ◽  
Ecg Signal ◽  
Interference Signal ◽  
Blind Source Extraction ◽  
Novel Approach ◽  
Power Line Noise ◽  
Power Line Interference ◽  
Line Noise

The cardiac signal is very important for the heart disease diagnosis and evaluation. The noise cancelation represent one of the most preprocessing step in ECG signal processing, usually, this signal is very sensitive and varies with time. The ECG signal is mostly contaminated by different signals like Power line noise signal, Baseline signal and muscle signal. The power line interference signal is the most effected signal on the ECG during data recording. Several papers try to cancel the noise based on different ways and to extract the useful information. In this paper a novel approach based on stone blind source extraction is used to extract the pure ECG signal from raw ECG, the main advantage of the proposed approach compared with the classical technique is to separate all the useful information without filtering or cancelling the suitable data from the recording signal. Real ECG data from MIT-BIH databases is taken and the MATLAB program is used to evaluate the experimental results. The performance of the proposed approach is measured based on SNR and MSE. The main contribution of this paper is to use Stone blind source separation technique as a first time in ECG signal analysis and prove that this method is the best technique compared with conventional ways. The obtained result proves Stone BSS technique is very efficient to remove the power line noise.

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