Vision-based calibration/compensation technique for automatic stiffener bonder

2016 ◽  
Vol 231 (1) ◽  
pp. 167-180 ◽  
Author(s):  
Su Ye ◽  
Yutang Ye ◽  
Yu Xie ◽  
Ying Luo ◽  
Chunlei Du
Keyword(s):  
Error Compensation ◽  
Least Squares Method ◽  
Error Model ◽  
Compensation Method ◽  
Calibration Error ◽  
Model Parameters ◽  
Coordinate Systems ◽  
Printed Circuit ◽  
Pick And Place ◽  
Flexible Printed Circuit

This study developed a novel error compensation method aimed at eliminating placement error caused by hand–eye calibration and pick-and-place tool motions in automatic stiffener bonder for flexible printed circuit. Using the transformation of homogeneous coordinates to develop an error model of the system describing the coupling of errors among various coordinate systems, the least squares method is used to calculate the unknown model parameters. The experiment results demonstrate that this error compensation method reduced placement error by an order of magnitude. The mounting precision throughout the entire work area was ±0.046 mm at 3sigma, and for flexible printed circuit products with a specification limit of 0.1 mm, the process capability index of the automatic stiffener bonder in this study was 2.19. This represents that the system is capable of fully satisfying the precision requirements of flexible printed circuit stiffener bonding. The proposed system employing a vibrating feeder bowl and machine vision–aided target positioning is applicable to a variety of stiffeners, which enhances production flexibility. The proposed error model considers the complex coupling effect of the errors among multiple coordinate systems in hand–eye calibration, without the need of detecting and calculating the calibration error item by item, and takes into account the errors produced by the rotation and downward pressing motions of the pick-and-place tool.

Study of error compensations and sensitivity analysis for 6-Dof serial robot

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xi Luo ◽  
Yingjie Zhang ◽  
Lin Zhang
Keyword(s):  
Sensitivity Analysis ◽  
Error Compensation ◽  
Error Model ◽  
Error Modeling ◽  
Compensation Method ◽  
Joint Clearance ◽  
Positioning Accuracy ◽  
Content Type ◽  
Model Based ◽  
Serial Robot

Purpose The purpose of this paper is to improve the positioning accuracy of 6-Dof serial robot by the way of error compensation and sensitivity analysis. Design/methodology/approach In this paper, the Denavit–Hartenberg matrix is used to construct the kinematics models of the robot; the effects from individual joint and several joints on the end effector are estimated by simulation. Then, an error model based on joint clearance is proposed so that the positioning accuracy at any position of joints can be predicted for compensation. Through the simulation of the curve path, the validity of the error compensation model is verified. Finally, the experimental results show that the error compensation method can improve the positioning accuracy of a two joint exoskeleton robot by nearly 76.46%. Findings Through the analysis of joint error sensitivity, it is found that the first three joints, especially joint 2, contribute a lot to the positioning accuracy of the robot, which provides guidance for the accuracy allocation of the robot. In addition, this paper creatively puts forward the error model based on joint clearance, and the error compensation method which decouples the positioning accuracy into joint errors. Originality/value It provides a new idea for error modeling and error compensation of 6-Dof serial robot. Combining sensitivity analysis results with error compensation can effectively improve the positioning accuracy of the robot, and provide convenience for welding robot and other robots that need high positioning accuracy.

scholarly journals A Novel Tri-Axial MEMS Gyroscope Calibration Method over a Full Temperature Range

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3004 ◽  
Author(s):  
Haotian Yang ◽  
Bin Zhou ◽  
Lixin Wang ◽  
Haifeng Xing ◽  
Rong Zhang
Keyword(s):  
Error Compensation ◽  
Least Squares Method ◽  
Reference Value ◽  
Calibration Method ◽  
Measurement Unit ◽  
Calibration Error ◽  
Error Matrix ◽  
Mems Gyroscope ◽  
Temperature Range ◽  
Full Temperature

The micro-electro-mechanical inertial measurement unit (MEMS-IMU) has gradually become a research hotspot in the field of mid-low navigation, because of its advantages of low cost, small size, light weight, and low power consumption (CSWap). However, the performance of MEMS-IMUs can be severely degraded when subjected to temperature changes, especially gyroscopes. In order to make full use of the navigation accuracy, this paper proposes an optimized error calibration method for a tri-axial MEMS gyroscope across a full temperature range. First of all, a calibration error model is established which includes package misalignment error, sensor-to-sensor non-orthogonality error, scale factor, and bias. Then, a simple three-position positive/reversed test is undertaken by carrying out a single-axis temperature-controlled turntable at different reference temperature points. Lastly, the error compensation vector is obtained using the least squares method to establish an error matrix. It is worth mentioning that the error compensation vector at a known temperature point can be calculated through Lagrange interpolation; then, the outputs of the tri-axial MEMS gyroscope can be well compensated, eliminating the need for a recalibration step. The experimental results confirm the effectiveness of the proposed method, which is feasible and operational in engineering applications, and has a certain reference value.

Centering Deviation Auto-Detection and Angle Measuring Error Compensation Method of Photoelectric Theodolite

2012 ◽  
Vol 151 ◽  
pp. 198-202
Author(s):  
Peng Cheng Pu ◽  
Xiao Song Guo ◽  
Zhao Fa Zhou ◽  
Kun Ming Wang
Keyword(s):  
Computer Vision ◽  
Error Compensation ◽  
Operation Time ◽  
Error Model ◽  
Compensation Method ◽  
Measuring Error ◽  
Compensation Model ◽  
Angle Measuring

The centering deviation auto-detection and angle measuring error compensation method based on computer vision was proposed in the paper, aim at the centering deviation in the process of measuring the angle. The effect law to angle measuring error by centering deviation was analyzed, and the error compensation model was founded, The value and direction of centering deviation was detected by CCD fixed on the surface below theodolite, then the angle measuring error by centering deviation could be compensated by the error model. The automation degree of angle measuring was improved and the operation time was reduced.

Constructing and model-fitting receiver operator characteristics using continuous data.

2018 ◽  
Author(s):  
Josephine Ann Urquhart ◽  
Akira O'Connor
Keyword(s):  
Signal Detection ◽  
Least Squares Method ◽  
Model Fitting ◽  
Simulated Data ◽  
Continuous Variable ◽  
Continuous Data ◽  
Model Parameters ◽  
Operating Characteristics ◽  
Unequal Variance ◽  
Discrete Discrimination

Receiver operating characteristics (ROCs) are plots which provide a visual summary of a classifier’s decision response accuracy at varying discrimination thresholds. Typical practice, particularly within psychological studies, involves plotting an ROC from a limited number of discrete thresholds before fitting signal detection parameters to the plot. We propose that additional insight into decision-making could be gained through increasing ROC resolution, using trial-by-trial measurements derived from a continuous variable, in place of discrete discrimination thresholds. Such continuous ROCs are not yet routinely used in behavioural research, which we attribute to issues of practicality (i.e. the difficulty of applying standard ROC model-fitting methodologies to continuous data). Consequently, the purpose of the current article is to provide a documented method of fitting signal detection parameters to continuous ROCs. This method reliably produces model fits equivalent to the unequal variance least squares method of model-fitting (Yonelinas et al., 1998), irrespective of the number of data points used in ROC construction. We present the suggested method in three main stages: I) building continuous ROCs, II) model-fitting to continuous ROCs and III) extracting model parameters from continuous ROCs. Throughout the article, procedures are demonstrated in Microsoft Excel, using an example continuous variable: reaction time, taken from a single-item recognition memory. Supplementary MATLAB code used for automating our procedures is also presented in Appendix B, with a validation of the procedure using simulated data shown in Appendix C.

scholarly journals Determination of synchronous generator nonlinear model parameters based on power rejection tests using a gradient optimization algorithm

2017 ◽  
Vol 65 (4) ◽  
pp. 479-488 ◽  
Author(s):  
A. Boboń ◽  
A. Nocoń ◽  
S. Paszek ◽  
P. Pruski
Keyword(s):  
Parameter Estimation ◽  
Objective Function ◽  
Optimization Algorithm ◽  
Least Squares Method ◽  
Synchronous Generator ◽  
Operating Conditions ◽  
Model Parameters ◽  
State Variables ◽  
Starting Point ◽  
Gradient Optimization

AbstractThe paper presents a method for determining electromagnetic parameters of different synchronous generator models based on dynamic waveforms measured at power rejection. Such a test can be performed safely under normal operating conditions of a generator working in a power plant. A generator model was investigated, expressed by reactances and time constants of steady, transient, and subtransient state in the d and q axes, as well as the circuit models (type (3,3) and (2,2)) expressed by resistances and inductances of stator, excitation, and equivalent rotor damping circuits windings. All these models approximately take into account the influence of magnetic core saturation. The least squares method was used for parameter estimation. There was minimized the objective function defined as the mean square error between the measured waveforms and the waveforms calculated based on the mathematical models. A method of determining the initial values of those state variables which also depend on the searched parameters is presented. To minimize the objective function, a gradient optimization algorithm finding local minima for a selected starting point was used. To get closer to the global minimum, calculations were repeated many times, taking into account the inequality constraints for the searched parameters. The paper presents the parameter estimation results and a comparison of the waveforms measured and calculated based on the final parameters for 200 MW and 50 MW turbogenerators.

scholarly journals Flexible Printed Circuit Board as Novel Electrodes for Acoustofluidic Devices

2020 ◽  
pp. 1-6
Author(s):  
Chao Sun ◽  
Roman Mikhaylov ◽  
Yongqing Fu ◽  
Fangda Wu ◽  
Hanlin Wang ◽  
...  
Keyword(s):  
Printed Circuit Board ◽  
Circuit Board ◽  
Printed Circuit ◽  
Flexible Printed Circuit
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