scholarly journals Analysis and Adjustment of Positioning Error of PSD System for Mobile SOF-FTIR

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5081
Author(s):  
Qu ◽  
Liu ◽  
Deng ◽  
Xu ◽  
Hu ◽  
...  
Keyword(s):  
Light Intensity ◽  
Dark Current ◽  
Detection System ◽  
Calibration Method ◽  
Positioning Error ◽  
Positioning Accuracy ◽  
Loop Control ◽  
Position Detection ◽  
Solar Tracking ◽  
Noise Factors

A PSD-based solar spot position detection system is developed for solar tracking closed-loop control of mobile SOF-FTIR (Solar Occultation Flux method based on Fourier Transform Infrared spectrometer). The positioning error factors of PSD (position sensitive detector) are analyzed in detail. A voltage model for PSD signal conditioning circuit has been established to investigate the noise factors. The model shows that the positioning error is mainly related to PSD dark current and circuit gain. A static voltage deduction calibration method based on genetic algorithm is proposed to eliminate the effect of dark current. The gain ratio between channels is calculated based on the fitting curve slope of discrete position data of PSD center point with different light intensity for circuit gain calibration. The positioning accuracy and precision are greatly enhanced, especially when the light intensity is weak, compared with uncalibrated results. The positioning accuracy of center, middle and edge areas of PSD can reach 0.14%, 0.49%, and 1.09%, respectively, after correction in the range of light intensity voltage from 40 mV to 20 V. The corresponding standard deviations of each region are 0.005, 0.009, and 0.014, respectively. The adjustment methods proposed in this paper improve both measurement accuracy and detection limit. The results demonstrate that the calibrated PSD positioning accuracy can meet the requirements of SOF-FTIR for solar tracking.

Dynamic and Positioning Performances of Linear Electromechanical Actuator

2015 ◽  
Vol 809-810 ◽  
pp. 682-687
Author(s):  
Vasile Nasui ◽  
Mihai Banica ◽  
Dinu Darabă
Keyword(s):  
Dynamic Characteristics ◽  
Practical Importance ◽  
Correct Identification ◽  
Positioning System ◽  
Positioning Error ◽  
Servo Motor ◽  
Positioning Accuracy ◽  
Electromechanical Actuator ◽  
Initial Errors ◽  
Selection For

This paper presents the dynamic characteristics and the proposed positioning performance of the system to them investigated experimentally. In this research, we developed the positioning system and we evaluated positioning accuracy. The developed system uses a servo motor for motion actuation. In this paper, we focused on studying the dependency of the positioning error – elementary errors – the position of the conducting element for the mechanism of the transformation of the rotation translation movement, representatively the mechanism screw – screwdriver and on emphasizing the practical consequences in the field of design, regulation and exploitation of the correct identification of all the initial errors in the structure of the mechanism, their character and the selection for an ultimate calculus of these which are of a real practical importance.

scholarly journals Research of Calibration Method for Industrial Robot Based on Error Model of Position

2021 ◽  
Vol 11 (3) ◽  
pp. 1287
Author(s):  
Tianyan Chen ◽  
Jinsong Lin ◽  
Deyu Wu ◽  
Haibin Wu
Keyword(s):  
Coordinate System ◽  
Industrial Robot ◽  
Calibration Method ◽  
Error Model ◽  
Position Error ◽  
Industrial Robots ◽  
Positioning Error ◽  
Robot Position ◽  
General Measurement ◽  
Parameter Error

Based on the current situation of high precision and comparatively low APA (absolute positioning accuracy) in industrial robots, a calibration method to enhance the APA of industrial robots is proposed. In view of the "hidden" characteristics of the RBCS (robot base coordinate system) and the FCS (flange coordinate system) in the measurement process, a comparatively general measurement and calibration method of the RBCS and the FCS is proposed, and the source of the robot terminal position error is classified into three aspects: positioning error of industrial RBCS, kinematics parameter error of manipulator, and positioning error of industrial robot end FCS. The robot position error model is established, and the relation equation of the robot end position error and the industrial robot model parameter error is deduced. By solving the equation, the parameter error identification and the supplementary results are obtained, and the method of compensating the error by using the robot joint angle is realized. The Leica laser tracker is used to verify the calibration method on ABB IRB120 industrial robot. The experimental results show that the calibration method can effectively enhance the APA of the robot.

scholarly journals Improvement of Heavy Load Robot Positioning Accuracy by Combining a Model-Based Identification for Geometric Parameters and an Optimized Neural Network for the Compensation of Nongeometric Errors

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yuxiang Wang ◽  
Zhangwei Chen ◽  
Hongfei Zu ◽  
Xiang Zhang ◽  
Chentao Mao ◽  
...  
Keyword(s):  
Neural Network ◽  
Manufacturing Systems ◽  
Robot Manipulator ◽  
Joint Stiffness ◽  
Calibration Method ◽  
Geometric Parameters ◽  
Heavy Load ◽  
Positioning Accuracy ◽  
Robot Positioning ◽  
Residual Errors

The positioning accuracy of a robot is of great significance in advanced robotic manufacturing systems. This paper proposes a novel calibration method for improving robot positioning accuracy. First of all, geometric parameters are identified on the basis of the product of exponentials (POE) formula. The errors of the reduction ratio and the coupling ratio are identified at the same time. Then, joint stiffness identification is carried out by adding a load to the end-effector. Finally, residual errors caused by nongeometric parameters are compensated by a multilayer perceptron neural network (MLPNN) based on beetle swarm optimization algorithm. The calibration is implemented on a SIASUN SR210D robot manipulator. Results show that the proposed method possesses better performance in terms of faster convergence and higher precision.

scholarly journals Gait Phase Detection Based on Muscle Deformation with Static Standing-Based Calibration

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1081
Author(s):  
Tamon Miyake ◽  
Shintaro Yamamoto ◽  
Satoshi Hosono ◽  
Satoshi Funabashi ◽  
Zhengxue Cheng ◽  
...  
Keyword(s):  
Learning Algorithm ◽  
Detection System ◽  
Calibration Method ◽  
Detection Algorithm ◽  
Video Data ◽  
Detection Accuracy ◽  
Phase Detection ◽  
Gait Phase ◽  
Logistic Regression Algorithm ◽  
Short Time

Gait phase detection, which detects foot-contact and foot-off states during walking, is important for various applications, such as synchronous robotic assistance and health monitoring. Gait phase detection systems have been proposed with various wearable devices, sensing inertial, electromyography, or force myography information. In this paper, we present a novel gait phase detection system with static standing-based calibration using muscle deformation information. The gait phase detection algorithm can be calibrated within a short time using muscle deformation data by standing in several postures; it is not necessary to collect data while walking for calibration. A logistic regression algorithm is used as the machine learning algorithm, and the probability output is adjusted based on the angular velocity of the sensor. An experiment is performed with 10 subjects, and the detection accuracy of foot-contact and foot-off states is evaluated using video data for each subject. The median accuracy is approximately 90% during walking based on calibration for 60 s, which shows the feasibility of the static standing-based calibration method using muscle deformation information for foot-contact and foot-off state detection.

Research on Calibration Method of Tire Dynamic Balance Detection System

2012 ◽  
Vol 542-543 ◽  
pp. 828-832 ◽  
Author(s):  
Jing Fang Yang ◽  
Xian Ying Feng ◽  
Hong Jun Fu ◽  
Lian Fang Zhao
Keyword(s):  
High Speed ◽  
Detection System ◽  
Dynamic Balance ◽  
Calibration Method ◽  
Engineering Practice ◽  
Influence Coefficient ◽  
Quality Factors ◽  
High Speed Rotation ◽  
Speed Rotation ◽  
Upper Rim

Tire dynamic balance detection plays an important part in tire quality detection area. This paper uses the two-sided balance method to obtain the unbalance of the tire. According to the engineering practice, builds kinetic model and then introduces the calculating principle and operating procedures. In order to accurately determine the influence coefficient, a calibration method without tire is put forward. Further more, this new method is able to eliminate the unbalance caused by non-quality factors to some extent. But this method is presented based on the relative position invariance of the upper rim and lower rim, even both of them are under high-speed rotation situation. Finally, the experimental data acquired from both of the two methods are compared. The calibration method without tire is proved to be more feasible, efficient and accurate.

Eye-position detection system

2000 ◽  
Author(s):  
Holger Heidrich ◽  
Armin Schwerdtner ◽  
Andreas Glatte ◽  
Hartmut Mix
Keyword(s):  
Detection System ◽  
Eye Position ◽  
Position Detection

scholarly journals Factor Graph-Assisted Distributed Cooperative Positioning Algorithm in the GNSS System

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3748 ◽  
Author(s):  
Chengkai Tang ◽  
Lingling Zhang ◽  
Yi Zhang ◽  
Houbing Song
Keyword(s):  
Smart Cities ◽  
Factor Graph ◽  
Positioning Error ◽  
Positioning Accuracy ◽  
Cooperative Positioning ◽  
Measured Range ◽  
Ranging Error ◽  
Positioning Algorithm ◽  
Range Error ◽  
Cooperative Nodes

The development of smart cities calls for improved accuracy in navigation and positioning services; due to the effects of satellite orbit error, ionospheric error, poor quality of navigation signals and so on, it is difficult for existing navigation technology to achieve further improvements in positioning accuracy. Distributed cooperative positioning technology can further improve the accuracy of navigation and positioning with existing GNSS (Global Navigation Satellite System) systems. However, the measured range error and the positioning error of the cooperative nodes exhibit larger reductions in positioning accuracy. In response to this question, this paper proposed a factor graph-aided distributed cooperative positioning algorithm. It establishes the confidence function of factor graphs theory with the ranging error and the positioning error of the coordinated nodes and then fuses the positioning information of the coordinated nodes by the confidence function. It can avoid the influence of positioning error and ranging error and improve the positioning accuracy of cooperative nodes. In the simulation part, the proposed algorithm is compared with a mainly coordinated positioning algorithm from four aspects: the measured range error, positioning error, convergence speed, and mutation error. The simulation results show that the proposed algorithm leads to a 30–60% improvement in positioning accuracy compared with other algorithms under the same measured range error and positioning error. The convergence rate and mutation error elimination times are only 1 / 5 to 1 / 3 of the other algorithms.

scholarly journals A New Efficient Stiffness Evaluation Method to Improve Accuracy of Hexapods

2018 ◽  
Author(s):  
Vinayak J. Kalas ◽  
Alain Vissière ◽  
Thierry Roux ◽  
Olivier Company ◽  
Sébastien Krut ◽  
...  
Keyword(s):  
Evaluation Method ◽  
Positioning System ◽  
Positioning Error ◽  
Stiffness Parameter ◽  
Positioning Accuracy ◽  
Stiffness Evaluation ◽  
Improve Accuracy ◽  
Identification Technique ◽  
Six Degree Of Freedom ◽  
Structural Compliance

Structural compliance of hexapods limits their positioning accuracy. Taking a step towards solving this problem, this paper proposes a new efficient method to evaluate the stiffness of hexapods in order to predict and correct their positioning error due to compliance. The proposed method can be used to predict the six degree of freedom deflection of the platform under load. This method uses a simple lumped stiffness parameter model whose parameters can be estimated using the identification technique presented in this paper. An experimental study with micrometer level measurements performed on a hexapod based micro-positioning system is used to assess the efficiency of the presented method.

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