scholarly journals DEM PARAMETERS CALIBRATION OF MIXED BIOMASS SAWDUST MODEL WITH MULTI-RESPONSE INDICATORS

2021 ◽  
pp. 183-192
Author(s):  
Gong Xun ◽  
Bai XueWei ◽  
Huang HaiBo ◽  
Zhang FengYu ◽  
Gong YuanJuan ◽  
...  
Keyword(s):  
Relative Error ◽  
Calibration Method ◽  
Rolling Friction ◽  
Test Scheme ◽  
Related Factors ◽  
Recovery Coefficient ◽  
Densification Mechanism ◽  
Calibration Experiment ◽  
Mixed Biomass ◽  
Response Indicators

Taking hybrid biomass sawdust as the material, carry out the simulation calibration experiment with JKR contact model based on DEM principle. The Plackett-Burman factorial experiment is carried out by Design-Expert for 10 related factors. Combined with the steepest climbing test scheme, according to the Box-Behnken experiment, the parameter calibration of the multi-response Indicators is completed. The results are as follows: the Poisson's ratio of hybrid sawdust is 0.30, the density is 399.22kg·m-3, the recovery coefficient between sawdust particles is 0.47, the rolling friction coefficient between sawdust particles is 0.39, and the parameter of surface energy density between sawdust particles (JKR) is 0.29J·m-2. Through the comparative verification experiment, it can be seen that the relative error of the repose angle is 3.41%, and the relative error of the stress-time response curve is less than 6.36%, which verifies the reliability of the calibration method, and provides a theoretical reference for the study of the constitutive characteristics of biomass materials and the densification mechanism.

scholarly journals INVESTIGATION OF M2044 VOLTAMMETER ERRORS FOR PERSPECTIVE IMPROVEMENT OF CALIBRATION METHOD

2018 ◽  
pp. 25-29
Author(s):  
M. S. Titova ◽  
K. V. Epifantsev ◽  
T. P. Mishura
Keyword(s):  
Relative Error ◽  
Calibration Method ◽  
Main Design ◽  
Calibration Time

The method of checking voltmeters and ammeters involves checking certain intervals on the tool scale, which requires a sufficient amount of time from the verifier engineer. In the considered graphs, which revealed repeated dependences of the main calibration errors on the calibration time. Therefore, this study is important to verify that it is not. The main design of the study was to improve the scale of the voltmeter based on the meter readings during meter calibration at Techpribor during the testing lab from 2016 to 2018. When studying the calibration graphs, jumps in the segment in the range from 40 to 90 V. It is assumed that an increase in the relative error provided that it was used for various fields of technology to improve the verification procedure for analog instruments. The marked interval should be checked on each scale mark on each limit.

scholarly journals Calibration and Verification of Dynamic Particle Flow Parameters by the Back-Propagation Neural Network Based on the Genetic Algorithm: Recycled Polyurethane Powder

Materials ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3350
Author(s):  
Ping He ◽  
Yiwei Fan ◽  
Banglong Pan ◽  
Yinfeng Zhu ◽  
Jing Liu ◽  
...  
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Friction Coefficient ◽  
Back Propagation ◽  
Static Friction ◽  
Discrete Element ◽  
Calibration Method ◽  
Angle Of Repose ◽  
Recovery Coefficient ◽  
Static Friction Coefficient

The discrete element method (DEM) is commonly used to study various powders in motion during transportation, screening, mixing, etc.; this requires several microscopic parameters to characterize the complex mechanical behavior of the particles. Herein, a new discrete element parameter calibration method is proposed to calibrate the ultrafine agglomerated powder (recycled polyurethane powder). Optimal Latin hypercube sampling and virtual simulation experiments were conducted using the commercial DEM software; the microscopic variables included the static friction coefficient between the particles, collision recovery coefficient, Johnson–Kendall–Roberts surface energy, static friction coefficient between the particles and wall, and collision recovery coefficient. A predictive model based on genetic-algorithm-optimized feedforward neural network (back propagation) was developed to calibrate the microscopic DEM simulation parameters. The cycle search algorithm and mean-shift cluster analysis were used to confirm the input parameters’ range by comparing the mean value of the dynamic angle of repose measured via the batch accumulation test. These parameters were verified by the baffle lifting method and the rotating drum method. This calibration method, once successfully developed, will be suitable for use in a variety of fine viscous powder dynamic flow conditions.

scholarly journals Calibration of DEM for Cohesive Particles in the SLS Powder Spreading Process

Processes ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1715
Author(s):  
Marco Lupo ◽  
Diego Barletta ◽  
Daniele Sofia ◽  
Massimo Poletto
Keyword(s):  
Surface Energy ◽  
Yield Strength ◽  
Calibration Method ◽  
Rolling Friction ◽  
Calibration Procedure ◽  
Testing Procedure ◽  
Angle Of Repose ◽  
Bulk Property ◽  
Static Testing ◽  
Experimental Values

In this paper, a new DEM calibration procedure based on two different types of procedures to compare simulation with experiments is proposed. The aim is to find the values of the interfacial adhesive surface energy and the coefficient of rolling friction between the particles to be used in the simulation. The approach adopted is the so-called Bulk Calibration method. The experimental values of the angle of repose and unconfined yield strength, found with a static testing method and by shear testing, respectively, are compared, respectively, with the angle of repose, found in a simulation reproducing the experimental procedure, and the unconfined yield strength, obtained from an idealized uniaxial testing procedure. The simulated DEM particles are spheres equipped with the Hertz Mindlin with JKR contact model. The results suggest that a bulk calibration approach is not able to provide results that are consistent with two simple bulk property evaluations and, therefore, direct ways to estimate the surface energy based on the evaluation of interparticle forces, for example, should preferably be adopted.

A Parameter Dimension Reduction-Based Estimation Approach to Enhance the Kinematic Accuracy of a Parallel Hardware-in-the-Loop Docking Simulator

Robotica ◽  
2020 ◽  
pp. 1-16
Author(s):  
Yan Hu ◽  
Feng Gao ◽  
Xianchao Zhao ◽  
Tianhao Yang ◽  
Haoran Shen ◽  
...  
Keyword(s):  
Docking Simulation ◽  
Calibration Method ◽  
Error Model ◽  
Error Modeling ◽  
Kinematic Calibration ◽  
Hardware In The Loop ◽  
Kinematic Accuracy ◽  
Calibration Experiment ◽  
Ground Test ◽  
Accuracy Performance

SUMMARY The hardware-in-the-loop docking simulators are significant ground test equipment for aerospace projects. The fidelity of docking simulation highly depends on the accuracy performance. This paper investigates the kinematic accuracy for the developed docking simulator. A novel kinematic calibration method which can reduce the number of parameters for error modeling is presented. The principle of parameters separation is studied. A simplified error model is derived based on Taylor series. This method can contribute to the simplification of the error model, fewer measurements, and easier convergence during the parameters identification. The calibration experiment validates this method for further accuracy enhancement.

scholarly journals Calibration of the Interaction Parameters between the Proppant and Fracture Wall and the Effects of These Parameters on Proppant Distribution

Energies ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 2099
Author(s):  
Mingzhong Li ◽  
Chunting Liu ◽  
Guodong Zhang
Keyword(s):  
Friction Coefficient ◽  
Critical Role ◽  
Three Dimensional ◽  
Static Friction ◽  
Calibration Method ◽  
Rolling Friction ◽  
Interaction Parameters ◽  
Wall Roughness ◽  
Proppant Transport ◽  
Equilibrium Height

Saltation and reputation (creep) dominate proppant transport rather than suspension during slickwater fracturing, due to the low sand-carrying capacity of the slickwater. Thus, the interaction parameters between proppants and fracture walls, which affect saltation and reputation, play a more critical role in proppant transport. In this paper, a calibration method for the interaction parameters between proppants and walls is built. A three-dimensional coupled computational fluid dynamics–discrete element method (CFD–DEM) model is established to study the effects of the interaction parameters on proppant migration, considering the wall roughness and unevenly distributed diameters of proppants. The simulation results show that a lower static friction coefficient and rolling friction coefficient can result in a smaller equilibrium height of the sand bank and a smaller build angle and drawdown angle, which is beneficial for carrying the proppant to the distal end of the fracture. The wall roughness and the unevenly distributed diameter of the proppants increase the collision between proppant and proppant or the wall, whereas the interactions have little impact on the sandbank morphology, slightly increasing the equilibrium height of the sandbank.

A flexible calibration method connecting the joint space and the working space of industrial robots

2018 ◽  
Vol 45 (3) ◽  
pp. 407-415 ◽  
Author(s):  
Ying Cai ◽  
Peijiang Yuan ◽  
Dongdong Chen
Keyword(s):  
Industrial Robot ◽  
Calibration Method ◽  
Joint Space ◽  
Position Error ◽  
Industrial Robots ◽  
Content Type ◽  
Position Errors ◽  
Working Space ◽  
Calibration Experiment ◽  
Control Command

Purpose To improve the accuracy of the industrial robots’ absolute positioning, a Kriging calibration is proposed. Design/methodology/approach This method particularly designs a semivariogram for connecting the joint space and the working space. After that, Kriging equations are determined and solved to predict the position errors of targets. Subsequently, a simple and convenient error compensation, which can be implemented on the control command, is proposed. Findings The verification experiment of the position-error multiplicity and the Kriging calibration experiment are done in the KUKA R210 R2700 industrial robot. The position-error multiplicity experiment reveals that the position error of the industrial robot varies with the joint angle sets. Besides, the Kriging calibration experiment shows that the maximum of the spatial position errors is reduced from 1.2906 to 0.2484 mm, which reveals the validity of the Kriging calibration. Originality/value The special designed semivariation allows this method to be flexible and practical. It can be used in various fields where the angle solutions of industrial robots should be adapted according to the optimal demand and the environment, such as the optimal trajectory planning and the obstacle avoidance. Besides, this method can provide accuracy positioning results.

scholarly journals Calibration-Free Robot-Sensor Calibration approach based on Second-Order Cone Programming

2018 ◽  
Vol 173 ◽  
pp. 02005 ◽  
Author(s):  
Li Wei ◽  
LU Naiguang ◽  
Dong Mingli ◽  
Lou Xiaoping
Keyword(s):  
Relative Error ◽  
Calibration Method ◽  
Second Order ◽  
Sensor Calibration ◽  
Camera Motion ◽  
Calibration Target ◽  
Cone Programming ◽  
Second Order Cone Programming ◽  
Second Order Cone ◽  
Calibration Free

In order to overcome the restrictions of traditional robot-sensor calibration method which solve the tool-camera transformation and robot-world transformation rely on calibration target, a calibration-free approach that solve the robot-sensor calibration problem of the form AX = YB based on Second-Order Cone Programming is proposed. First, a Structure-From-Motion approach was used to recover the camera motion matrix up to scaling. Then rotation and translation matrix in calibration equation were parameterized by dual quaternion theory. Finally, the Second-Order Cone Programming method was used to simultaneously solve the optimal solution of camera motion matrix scale factor, the robot-world and hand-eye relation. The experimental results indicate that the calibration precision of rotation relative error is 3.998% and the translation relative error is 0.117% in defect of calibration target as 3D benchmark. Compared with similar methods, the proposed method can effectively improve the calibration accuracy of the robot-world and hand-eye relation, and extend the application field of robot-sensor calibration method.

The Research on the Static Calibration of Fingertip Force Sensor for Underwater Dexterous Hand on RBF Neural Network

2007 ◽  
Vol 10-12 ◽  
pp. 267-270
Author(s):  
Peng Jia ◽  
Qing Xin Meng ◽  
Hua Wang ◽  
Hai Bo Wang
Keyword(s):  
Neural Network ◽  
Rbf Neural Network ◽  
Force Sensor ◽  
Calibration Method ◽  
Complex Task ◽  
Calibration System ◽  
Static Calibration ◽  
Fingertip Force ◽  
Calibration Experiment ◽  
Dexterous Hand

The fingertip force sensor is the key for the complex task of the dexterous underwater hand, in order to safely grasp an unknown object using the dexterous underwater hand and accurately perceive its position in the fingers, a sensor should be developed, which can detect the force and position simultaneously. Furthermore, this sensor should be used underwater. It is difficult to employ the accustomed calibration method for the characteristic of the fingertip force sensor, and the accustomed method is not able to assure the precision. A calibration method based on RBF (Radial-Basis Function) neural network is introduced. Furthermore, the calibration system and program are also designed. The calibration experiment of the sensor is carried out. The results show the nonlinear calibration method based on RBF neural network assure the precision of the sensor, which meets the demand of research on the underwater dexterous hand.

A Calibration Method of Binocular Stereo Vision System Based on Halcon

2014 ◽  
Vol 989-994 ◽  
pp. 3007-3010
Author(s):  
Zhi Xian Zhang ◽  
Zhen De Zhu
Keyword(s):  
Stereo Vision ◽  
Vision System ◽  
Calibration Method ◽  
Pinhole Camera ◽  
Camera Model ◽  
Stereo Vision System ◽  
Imaging Model ◽  
Binocular Stereo Vision ◽  
Calibration Experiment ◽  
Binocular Stereo

This paper describes the pinhole camera model combined with an area sensor and a regular lens and the imaging model of the binocular stereo vision system. Also a method to determine the internal and external parameters of a camera by transferring the coordinates three times is described. Then a calibration experiment is carried out with the Halcon calibration board which proved the method works. The method mentioned in this paper has laid a good foundation for measuring the size of objects with the binocular stereo vision system.

Practical Importance of Spatial Resolution and Analytical Sensitivity in AEM X-ray Microanalysis

1990 ◽  
Vol 48 (2) ◽  
pp. 432-433
Author(s):  
J. Zhang ◽  
D.B. Williams ◽  
J.I. Goldstein
Keyword(s):  
Spatial Resolution ◽  
Practical Importance ◽  
Beam Current ◽  
Specimen Thickness ◽  
Analytical Sensitivity ◽  
Related Factors ◽  
X Ray ◽  
Probe Size ◽  
Excitation Volume ◽  
Two Parameters

Analytical sensitivity and spatial resolution are important and closely related factors in x-ray microanalysis using the AEM. Analytical sensitivity is the ability to distinguish, for a given element under given conditions, between two concentrations that are nearly equal. The analytical sensitivity is directly related to the number of x-ray counts collected and, therefore, to the probe current, specimen thickness and counting time. The spatial resolution in AEM analysis is determined by the probe size and beam broadening in the specimen. A finer probe and a thinner specimen give a higher spatial resolution. However, the resulting lower beam current and smaller X-ray excitation volume degrade analytical sensitivity. A compromise must be made between high spatial resolution and an acceptable analytical sensitivity. In this paper, we show the necessity of evaluating these two parameters in order to determine the low temperature Fe-Ni phase diagram.A Phillips EM400T AEM with an EDAX/TN2000 EDS/MCA system and a VG HB501 FEG STEM with a LINK AN10 EDS/MCA system were used.

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