Modeling and Error Compensation of MEMS Gyroscope Dynamic Output Data within the Whole Temperature Range

2011 ◽  
Vol 311-313 ◽  
pp. 768-771 ◽  
Author(s):  
Yan Shun Zhang ◽  
Shu Wei Wang
Keyword(s):  
Data Model ◽  
Rbf Neural Network ◽  
Performance Testing ◽  
High Accuracy ◽  
Output Data ◽  
Mems Gyroscope ◽  
Temperature Range ◽  
Dynamic Output ◽  
C 50 ◽  
Experimental Data Collection

In this paper, the output data of MEMS gyroscope ADRX150 under different input angular velocity within the temperature range of -30°C~50°C is collected and analyzed. Taking the nonlinear and random characteristics of the output data of MEMS gyroscope ADRX150 into account, the dynamic output data model based on RBF neural network is established, which is training and taking the performance testing with the experimental data collection. The results indicate that, the model has high accuracy and good generalization ability.

Technique and results of experimental determination of the compressibility factor of the natural gas

2021 ◽  
pp. 35-40
Author(s):  
Denis Y. Kutovoy ◽  
Igor A. Yatsenko ◽  
Vladimir B. Yavkin ◽  
Aydar N. Mukhametov ◽  
Petr V. Lovtsov ◽  
...  
Keyword(s):  
Natural Gas ◽  
Equations Of State ◽  
Compressibility Factor ◽  
High Accuracy ◽  
State Equations ◽  
Actual Problem ◽  
Temperature Range ◽  
Relative Value ◽  
Compressibility Coefficient

The actual problem of the possibility of using the equations of state for the gas phase of natural gas at temperatures below 250 K is considered. To solve it, the compressibility coefficients of natural gas obtained experimentally with high accuracy are required. The technique was developed and experimental study was carried out of compressibility factor aiming expanding temperature range of the state equations GERG-2004 and AGA8-DC92. The proposed technique is based on the fact that to assess the applicability of the equation of state, it is sufficient to obtain the relative value of the compressibility coefficient and not to determine its absolute value. The technique does not require complex equipment and provides high accuracy. The technique was tested on nitrogen, argon, air and methane. Uncertainty of determination of the compressibility factor is not greater than 0.1 %. For two different compositions of natural gas, obtained experimental data were demonstrated that the equations of state GERG-2004 and AGA8-92DC provide uncertainty of the calculation of the compressibility coefficient within 0.1 % in the temperature range from 220 K to 250 K and pressure below 5 MPa.

Chaotic motion control of a vibro-impact system based on data-driven control method

2021 ◽  
pp. 107754632110433
Author(s):  
Xiao-juan Wei ◽  
Ning-zhou Li ◽  
Wang-cai Ding
Keyword(s):  
Motion Control ◽  
Data Model ◽  
Chaotic Motion ◽  
Control Method ◽  
Data Driven ◽  
Damping Coefficient ◽  
Input Output ◽  
Output Data ◽  
Controlled System ◽  
Impact System

For the chaotic motion control of a vibro-impact system with clearance, the parameter feedback chaos control strategy based on the data-driven control method is presented in this article. The pseudo-partial-derivative is estimated on-line by using the input/output data of the controlled system so that the compact form dynamic linearization (CFDL) data model of the controlled system can be established. And then, the chaos controller is designed based on the CFDL data model of the controlled system. And the distance between two adjacent points on the Poincaré section is used as the judgment basis to guide the controller to output a small perturbation to adjust the damping coefficient of the controlled system, so the chaotic motion can be controlled to a periodic motion by dynamically and slightly adjusting the damping coefficient of the controlled system. In this method, the design of the controller is independent of the order of the controlled system and the structure of the mathematical model. Only the input/output data of the controlled system can be used to complete the design of the controller. In the simulation experiment, the effectiveness and feasibility of the proposed control method in this article are verified by simulation results.

scholarly journals High accuracy magnetic field sensors with wide operation temperature range

2016 ◽  
Vol 151 ◽  
pp. 012029
Author(s):  
I S Vasil'evskii ◽  
A N Vinichenko ◽  
D I Rubakin ◽  
I A Bolshakova ◽  
N I Kargin
Keyword(s):  
Magnetic Field ◽  
High Accuracy ◽  
Magnetic Field Sensors ◽  
Temperature Range ◽  
Operation Temperature

Integrated management of facility, process, and output: data model perspective

2012 ◽  
Vol 55 (5) ◽  
pp. 994-1007 ◽  
Author(s):  
Seunghoon Lee ◽  
Soonhung Han ◽  
Duhwan Mun
Keyword(s):  
Data Model ◽  
Integrated Management ◽  
Output Data

A Special Nonlinear Processing Method of Precise Digital Temperature Measurement with Platinum Thermistor

2012 ◽  
Vol 562-564 ◽  
pp. 1745-1748
Author(s):  
Gang Li
Keyword(s):  
Temperature Measurement ◽  
High Accuracy ◽  
Processing Method ◽  
Medium Temperature ◽  
Temperature Range ◽  
Nonlinear Processing ◽  
Common Components

The nonlinear rectifying method is widely used for improving the accuracy of temperature measurement. Using industrial platinum thermistor, DT-1000 digital multi-meter and other common components, a special nonlinear processing method puts forward to achieving high accuracy digital temperature measurement within the medium temperature range. The result shows the effectiveness of the method.

Preparation of polyurethanes with broad damping temperature range and self-healing properties

2019 ◽  
Vol 52 (5) ◽  
pp. 410-431 ◽  
Author(s):  
Xun Lu ◽  
Min Xu ◽  
Ye-ming Sheng ◽  
Zhi-peng Li ◽  
Han-mo Li
Keyword(s):  
Hydrogen Bonding ◽  
Synergistic Effect ◽  
Microphase Separation ◽  
Monomethyl Ether ◽  
Self Healing ◽  
Temperature Range ◽  
Healing Property ◽  
Tan Δ ◽  
C 50 ◽  
Damping Materials

It is urgent for polyurethane (PU) damping materials to broaden the effective damping range. Based on the designability of PU, this study is focused on the role of long dangling chain, wherein prepared by the reaction of polyethylene glycol monomethyl ether with toluene-2,4-diisocyanate. Notably, the introduction of long dangling chain not only makes the dangling chain longer and enhances the intermolecular interaction but also equips the dangling chain with strong polar carbamate group, bringing about more excellent compatibility of the soft and hard segments and lower degree of microphase separation under the condition of hydrogen bonding. The results show that the damping performance increases with the synergistic effect of significant hydrogen bonding and decreased degree of microphase separation, and the effective damping temperature range (tan δ ≥ 0.3) can exceed 150°C (−50°C to 100°C). Simultaneously, the addition of long dangling chains endows PU with self-healing property, the self-healing rate of system reaches maximum 70% with shore A hardness of 15 because of the synergistic effect above with the addition of 60% dangling chain, which extends the service life of PU damping materials.

Comparative Research on Attitude Algorithm of the Multi-Rotor UAV Based on the Gyroscope

2014 ◽  
Vol 651-653 ◽  
pp. 668-671
Author(s):  
Xin Zhang ◽  
Lan Yu
Keyword(s):  
Comparative Research ◽  
High Reliability ◽  
Euler Angle ◽  
High Accuracy ◽  
Mems Gyroscope ◽  
Autonomous Flight ◽  
Attitude Angle ◽  
The Stability ◽  
Mean Square Errors ◽  
Angle Calculation

Obtaining the flight attitude of high accuracy, high reliability is a prerequisite for achieving the autonomous flight of the multi-rotor UAV. MEMS gyroscope can solve attitude angle individually. The paper adopts Euler angle and quaternion algorithms respectively to calculate attitude angle of the multi-rotor UAV. The flight experiment shows that the quaternion algorithm can guarantee the accuracy and the stability of the attitude angle calculation. The root-mean-square errors of the pinch roll and heading angles which are calculated by the quaternion algorithm are 2.947o, 3.606o and 9.769o, which can meet the demand for the autonomous flight of the multi-rotor UAV.

Damage Identification of Structure Based on RBF Neural Network

2013 ◽  
Vol 753-755 ◽  
pp. 2356-2359
Author(s):  
Cheng Gang Zhen ◽  
Xiang Ting Chong
Keyword(s):  
Neural Network ◽  
Least Squares ◽  
Health Monitoring ◽  
Damage Identification ◽  
Rbf Neural Network ◽  
High Accuracy ◽  
Learning Method ◽  
Test Results ◽  
Health Monitoring System ◽  
Orthogonal Least Squares

Health monitoring of the structure is a topic widely concerned and researched in the fields of technology and engineering at home and abroad. Damage identification of structure is an important aspect of the whole health monitoring system. In this paper, the RBF neural network with the effect of bionic is used to the extent, location and area recognition of the damage on the structure with single damage. The method of orthogonal least squares (OLS) is used as the learning method of the network. The test results show that the RBF neural network and the learning method of OLS can identify the damage status of the structure quickly and effectively with high accuracy.

scholarly journals System Identification of a MEMS Gyroscope

1999 ◽  
Vol 123 (2) ◽  
pp. 201-210 ◽  
Author(s):  
Robert T. M’Closkey ◽  
Steve Gibson ◽  
Jason Hui
Keyword(s):  
System Identification ◽  
Angular Rate ◽  
Experimental System ◽  
Primary Objective ◽  
Input Output ◽  
Output Data ◽  
Mems Gyroscope ◽  
Principal Axes ◽  
Frequency Split ◽  
Insight Into

This paper reports the experimental system identification of the Jet Propulsion Laboratory MEMS vibratory rate gyroscope. A primary objective is to estimate the orientation of the stiffness matrix principal axes for important sensor dynamic modes with respect to the electrode pick-offs in the sensor. An adaptive lattice filter is initially used to identify a high-order two-input/two-output transfer function describing the input/output dynamics of the sensor. A three-mode model is then developed from the identified input/output model to determine the axes’ orientation. The identified model, which is extracted from only two seconds of input/output data, also yields the frequency split between the sensor’s modes that are exploited in detecting the rotation rate. The principal axes’ orientation and frequency split give direct insight into the source of quadrature measurement error that corrupts detection of the sensor’s angular rate.

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