Force/Moment Isotropy of 8/4-4 Parallel Six-Axis Force Sensor Based on Performance Atlases

A six-axis force sensor with parallel 8/4-4 structure is introduced and its measurement principle is analyzed.Based on condition numbers of Jacobian matrix spectral norm of the sensor,the relationship between the force and moment isotropy and some structural parameters is deduced.Orthogonal test methods are used to determine the degree of primary and secondary factors that have significant effect on sensor characteristics.Furthermore,the relationship between each performance index and the structural parameters of the sensor is analyzed by the method of the atlas,which lays a foundation for structural optimization design of the force sensor.

A novel fully-integrated miniature six-axis force/torque sensor

This paper presents a new designed miniature six DOF （degree of freedom） force/torque sensor. This sensor is fully integrated with a micro DSP （digital signal processor）, so all the signal conditioning, A/D, decoupling, digital-signals serial output are performed in the sensor. Some experimental results are presented to demonstrate the capability of the proposed design. Finally, a neural network was used for decoupling the interacting signals, compared with the conventional method using the inverse matrix, this new method is more accurate.

Dynamic analysis of double-layer and pre-stressed multi-limb six-axis force sensor

In order to adapt to the specific task, the six-axis dynamic contact force between end-effectors of intelligent robots and working condition needs to be perceived. Therefore, the dynamic property of six-axis force sensor which is installed on the end-effectors of intelligent robots will have influence on the veracity of detection and judgment to working environment contact force by intelligent robots directly. In this paper, dynamic analysis to double-layer and pre-stressed multi-limb six-axis force sensor is conducted. First, the structure of the sensor is introduced, and the limb number is confirmed by introducing the related definitions of convex analysis. Then, based on vibration of multiple-degree-of-freedom system, a mechanical vibration simplified model of double-layer and pre-stressed multiple limb six-axis force sensor is set up. After that, movement differential equations of sensor and the response of analytical expression are deduced, and the movement differential equations is solved. Finally, taking the double-layer and pre-stressed seven limb six-axis force sensor as an example, numerical calculation and simulation of deriving result is conducted, which verify the correctness and feasibility of the theoretical analysis.

Optimal design and experiment research of an orthogonal-parallel six-axis force/torque sensor

A novel orthogonal-parallel six-axis force/torque sensor is studied based on a modified Stewart platform architecture,and the optimal design and experiment research of the sensor are discussed.Firstly,the model of orthogonal parallel six-axis force/torque sensor based on improved Stewart platform architecture and its static mathematical model are proposed.Secondly,according to the actual working condition of the sensor,the sensor is optimized and the optimal solution is obtained.Then,the experimental prototype and calibration system is developed.Finally,the superiority of the sensor structure and the effectiveness of the optimization method are verified by calibration experiments.The results of the proposed method are useful for the further research and application of the orthogonal-parallel six-axis force/torque sensor.

Feature Fusion-Based Deep Learning Network to Recognize Table Tennis Actions

A system for classifying four basic table tennis strokes using wearable devices and deep learning networks is proposed in this study.The wearable device consisted of a six-axis sensor,Raspberry Pi 3,and a power bank.Multiple kernel sizes were used in convolutional neural network(CNN)to evaluate their performance for extracting features.Moreover,a multiscale CNN with two kernel sizes was used to perform feature fusion at different scales in a concatenated manner.The CNN achieved recognition of the four table tennis strokes.Experimental data were obtained from20 research participants who wore sensors on the back of their hands while performing the four table tennis strokes in a laboratory environment.The data were collected to verify the performance of the proposed models for wearable devices.Finally,the sensor and multi-scale CNN designed in this study achieved accuracy and F1 scores of 99.58%and 99.16%,respectively,for the four strokes.The accuracy for five-fold cross validation was 99.87%.This result also shows that the multi-scale convolutional neural network has better robustness after fivefold cross validation.

Analysis and modeling of error of spiral bevel gear grinder based on multi-body system theory

Six-axis numerical control spiral bevel gear grinder was taken as the object, multi-body system theory and Denavit-Hartenberg homogeneous transformed matrix （HTM） were utilized to establish the grinder synthesis error model, and the validity of model was confirmed by the experiment. Additionally, in grinding wheel tool point coordinate system, the errors of six degrees of freedom were simulated when the grinding wheel revolving around C-axis, moving along X-axis and Y-axis. The influence of these six errors on teeth space, helix angle, pitch, teeth profile was discussed. The simulation results show that the angle error is in the range from -0.148 4 tad to -0.241 9 rad when grinding wheel moving along X, Y-axis; the translation error is in the range from 0.866 0 μm to 3.605 3μm when grinding wheel moving along X-axis. These angle and translation errors have a great influence on the helix angle, pitch, teeth thickness and tooth socket.

Aerodynamic drag analysis of double-deck container vehicles with different structures

To study the aerodynamic performance of a new six-axis X2K double-deck container vehicle, numerical simulation was done based on three-dimensional, steady Navier-Stokes equations and k-e turbulence model. The results show that the pressure on the front surface of vehicle is positive, and others are negative. The maximum negative one appears as a ＂gate＂ shape on front surfaces. The pressure on vehicle increases with train speed, and pressure on vehicles with cross-loaded structure is smaller than that without it. The airflow around vehicles is symmetrical about train vertical axis, and the flow velocity decreases gradually along the axis to ground. Airflow around vehicles with cross-loaded structure is weaker than that without the structure. The aerodynamic drag increases linearly with the train speed, and it is minimum for the mid-vehicle. The linear coefficient for mid-vehicle without cross-loaded structure is 29.75, nearly one time larger than that with the structure valued as 15.425. So, from the view-point of aerodynamic drag, the cross-loaded structure is more reasonable for the six-axis X2K double-deck container vehicle.