scholarly journals An Online Calibration Method for a Galvanometric System Based on Wavelet Kernel ELM

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1353 ◽  
Author(s):  
Wugang Zhang ◽  
Wei Guo ◽  
Chuanwei Zhang ◽  
Shuanfeng Zhao
Keyword(s):  
Real Time ◽  
Calibration Method ◽  
System Structure ◽  
Data Sets ◽  
Position Measurement ◽  
Online Calibration ◽  
Time Performance ◽  
Calibration Methods ◽  
Testing Data ◽  
Mean Square Errors

The online calibration method of a two-dimensional (2D) galvanometer requires both high precision and better real-time performance to meet the needs of moving target position measurement, which presents some challenges for traditional calibration methods. In this paper, a new online calibration method is proposed using the wavelet kernel extreme learning machine (KELM). Firstly, a system structure is created and its experiment setup is established. The online calibration method is then analyzed based on a wavelet KELM algorithm. Finally, the acquisition methods of the training data are set, two groups of testing data sets are presented, and the verification method is described. The calibration effects of the existing methods and wavelet KELM methods are compared in terms of both accuracy and speed. The results show that, for the two testing data sets, the root mean square errors (RMSE) of the Mexican Hat wavelet KELM are reduced by 16.4% and 38.6%, respectively, which are smaller than that of the original ELM, and the standard deviations (Sd) are reduced by 19.2% and 36.6%, respectively, indicating the proposed method has better generalization and noise suppression performance for the nonlinear samples of the 2D galvanometer. Although the online operation time of KELM is longer than ELM, due to the complexity of the wavelet kernel, it still has better real-time performance.

A Self-Calibration Method for Robotic Measurement System

1999 ◽  
Author(s):  
Chunhe Gong ◽  
Jingxia Yuan ◽  
Jun Ni
Keyword(s):  
Coordinate System ◽  
Measurement System ◽  
Calibration Method ◽  
Position Measurement ◽  
Robot Calibration ◽  
Robot System ◽  
Self Calibration ◽  
World Coordinate System ◽  
Robot Accuracy ◽  
Calibration Methods

Abstract Robot calibration plays an increasingly important role in manufacturing. For robot calibration on the manufacturing floor, it is desirable that the calibration technique be easy and convenient to implement. This paper presents a new self-calibration method to calibrate and compensate for robot system kinematic errors. Compared with the traditional calibration methods, this calibration method has several unique features. First, it is not necessary to apply an external measurement system to measure the robot end-effector position for the purpose of kinematic identification since the robot measurement system has a sensor as its integral part. Second, this self-calibration is based on distance measurement rather than absolute position measurement for kinematic identification; therefore the calibration of the transformation from the world coordinate system to the robot base coordinate system, known as base calibration, is not necessary. These features not only greatly facilitate the robot system calibration but also shorten the error propagation chain, therefore, increase the accuracy of parameter estimation. An integrated calibration system is designed to validate the effectiveness of this calibration method. Experimental results show that after calibration there is a significant improvement of robot accuracy over a typical robot workspace.

scholarly journals HYBRID ONLINE MOBILE LASER SCANNER CALIBRATION THROUGH IMAGE ALIGNMENT BY MUTUAL INFORMATION

2016 ◽  
Vol III-1 ◽  
pp. 25-31 ◽  
Author(s):  
Mourad Miled ◽  
Bahman Soheilian ◽  
Emmanuel Habets ◽  
Bruno Vallet
Keyword(s):  
Mutual Information ◽  
Imaging System ◽  
Laser Scanner ◽  
Point Clouds ◽  
Calibration Method ◽  
Online Calibration ◽  
Calibration Methods ◽  
Laser Calibration ◽  
Scanner Calibration

This paper proposes an hybrid online calibration method for a laser scanner mounted on a mobile platform also equipped with an imaging system. The method relies on finding the calibration parameters that best align the acquired points cloud to the images. The quality of this intermodal alignment is measured by Mutual information between image luminance and points reflectance. The main advantage and motivation is ensuring pixel accurate alignment of images and point clouds acquired simultaneously, but it is also much more flexible than traditional laser calibration methods.

scholarly journals Online Calibration Method for Current Sensors Based on GPS

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 1923
Author(s):  
Shuang Zhao ◽  
Jun Liu ◽  
Yansong Li
Keyword(s):  
Calibration Method ◽  
National Standard ◽  
Economic Losses ◽  
Current Sensor ◽  
Sensor Calibration ◽  
Gps Receiver ◽  
Angular Difference ◽  
Online Calibration ◽  
Calibration Methods ◽  
Current Sensors

At present, most sensor calibration methods are off-line calibration, which not only makes them time-consuming and laborious, but also causes considerable economic losses. Therefore, in this study, an online calibration method of current sensors is proposed to address the abovementioned issues. The principle and framework of online calibration are introduced. One of the calibration indexes is angular difference. In order to accurately verify it, data acquisition must be precisely synchronized. Therefore, a precise synchronous acquisition system based on GPS timing is proposed. The influence of ionosphere on the accuracy of GPS signal is analyzed and a new method for measuring the inherent delay of GPS receiver is proposed. The synchronous acquisition performance of the system is verified by inter-channel synchronization experiment, and the results show that the synchronization of the system is accurate. Lastly, we apply our online calibration method to the current sensor; the experimental results show that the angular difference and ratio difference meet the requirements of the national standard and the accuracy of the online calibration system can be achieved to 0.2 class, demonstrating the effectiveness of the proposed online calibration method.

Integrated Method for Online Calibration of Real-Time Traffic Network Management Systems

2015 ◽  
Vol 2528 (1) ◽  
pp. 106-115 ◽  
Author(s):  
Hossein Hashemi ◽  
Khaled Abdelghany
Keyword(s):  
Network Management ◽  
Real Time ◽  
Simulation Models ◽  
Calibration Method ◽  
Propagation Model ◽  
Traffic Network ◽  
Operational Conditions ◽  
Online Calibration ◽  
Integrated Method ◽  
Real Time Traffic

This paper presents an integrated method for online calibration of realtime traffic network simulation models. The method integrates a time-dependent demand adjustment module and a link-based traffic flow propagation model calibration module. These modules use available realtime traffic observations to minimize inconsistency between the model estimation results and real-world observations. The modules are integrated into a real-time traffic network management system that was developed for the US-75 corridor in Dallas, Texas. Results illustrate that the online calibration method is effective in enhancing the model's consistency in the different operational conditions.

Framework for Multivariate Selectivity Analysis, Part I: Theoretical and Practical Merits

2005 ◽  
Vol 59 (6) ◽  
pp. 787-803 ◽  
Author(s):  
Christopher D. Brown ◽  
Trent D. Ridder
Keyword(s):  
Near Infrared ◽  
Clinical Laboratory ◽  
Simulated Data ◽  
Calibration Method ◽  
National Committee ◽  
Data Sets ◽  
Calibration Methods ◽  
Inverse Calibration ◽  
The One ◽  
Definition Of

A number of definitions of multivariate selectivity have been proposed in the literature. Arguably, the one that enjoys the greatest chemometric attention has been the net analyte signal (NAS) based definitions of Lorber and Zinn. Recent works have suggested that similar inference can be made for inverse least-squares calibration methods (e.g., principal components regression). However, the properties of inverse calibration methods are markedly different than classical methods, so in many practical cases involving inverse models classically derived figures of merit cannot be transparently interpreted. In Part I of this work, we discuss a selectivity framework that is theoretically consistent regardless of the calibration method. Importantly, it is also experimentally measurable, either through controlled selectivity experiments, or through analysis on opportunistically acquired sample measurements. It is statistically advantageous to use the former if such control is achievable. Selectivity is defined to be a function of the change in predicted analyte concentration that will result from a change in the concentration of an interferant, an approach consistent with traditional definitions of analytical selectivity and National Committee for Clinical Laboratory Standards recommendations for interference testing. Unlike the NAS-based definition of selectivity, the definition discussed herein is relevant to only a particular analyte–interferant pair. The theoretical and experimental aspects of this approach are illustrated with simulated data herein and in Part II of this paper, which investigates several experimental near-infrared data sets.

Wavelength Calibration Methods for Low-Resolution Photodiode Array Spectrometers

1993 ◽  
Vol 47 (7) ◽  
pp. 1007-1014 ◽  
Author(s):  
J. Thomas Brownrigg
Keyword(s):  
Measurement Errors ◽  
Calibration Method ◽  
Spectral Lines ◽  
Low Resolution ◽  
Position Measurement ◽  
Wavelength Calibration ◽  
Regression Methods ◽  
Calibration Methods ◽  
Wavelength Pair ◽  
Pair Method

A wavelength calibration method for low-resolution diode array spectrometers is described. The method was developed for routine calibration of 0.1-meter-focal-distance spectrometers having 35- or 38-element silicon diode arrays, normally operated in the 340–700 nm spectral range. Each diode of the array is approximately 1 mm wide, giving an instrumental bandwidth of ∼10 nm per diode. The calibration method requires two well-separated monochromatic spectral lines, their central image locations on the array, and the grating groove frequency. This method is compared with nonlinear regression (least-squares) methods, with multiple calibration lines fitted to quadratic or cubic polynomials. The predictive accuracy of the wavelength-pair method compares favorably with the regression methods. A calibration accuracy of ∼±1 nm is expected for the instruments considered here. The method described could, in principle, be applied to instruments with higher resolution, such as those having self-scanned photodiode arrays with 25-μm or 50-μm-wide pixels. For such instruments, however, a large number of calibration lines should be resolved. In this case, the regression method, which averages diode position measurement errors, is probably more accurate. The wavelength-pair method is most useful for low-resolution instruments, for which regression methods may not be practical.

Real-Time Estimation and Calibration of GLONASS Inter-Frequency Phase and Code Bias

2019 ◽  
Vol 73 (3) ◽  
pp. 746-762 ◽  
Author(s):  
Zhixin Yang ◽  
Hui Liu ◽  
Yidong Lou ◽  
Bao Shu ◽  
Longwei Xu ◽  
...  
Keyword(s):  
Real Time ◽  
Elevation Angle ◽  
Vertical Direction ◽  
Time Estimation ◽  
Calibration Method ◽  
Mean Value ◽  
Time Calibration ◽  
Calibration Methods ◽  
Code Bias ◽  
Frequency Phase

The frequency division multiple access (FDMA) strategy used in GLONASS causes inter-frequency phase bias (IFPB) and inter-frequency code bias (IFCB) between receivers from different manufacturers. The existence of IFPB and IFCB significantly increases the difficulties of fixing GLONASS ambiguity and limits the accuracy and reliability of GLONASS positioning. Moreover, the initial value of IFPB and IFCB may be unavailable or unreliable with the increasing number of receivers from different manufacturers in recent years. In this study, a real-time and reliable calibration algorithm of IFPB and IFCB based on multi-GNSS assistance is proposed by providing a fixed solution. Real-time IFPB rate and IFCB can be obtained using this algorithm without the initial IFPB and IFCB. The IFPB rate for all GLONASS satellites and IFCB for each GLONASS satellite are estimated due to different characteristics of IFPB and IFCB. IFPB calibration can be divided into constant and real-time IFPB calibrations to meet the different positioning requirements. Results show that constant IFPB rate has only 2 mm difference from the mean value of real-time IFPB rate. The IFPB rate and IFCB estimated by this algorithm have excellent stability, and the change in reference satellite cannot affect the results of IFPB rate and the stability of IFCB. The centimetre-level positioning results can be obtained using two calibration methods, and the positioning results with real-time calibration method are 10%–20% better than those with the constant calibration method. Under satellite-deprived environments, the improvements of multi-GNSS positioning accuracy with constant inter-frequency bias calibration gradually increase as the satellite cut-off elevation angle increases compared with GPS/BDS, which can reach up to 0·9 cm in the vertical direction.

scholarly journals A Hough-Space-Based Automatic Online Calibration Method for a Side-Rear-View Monitoring System

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3407
Author(s):  
Jung Hyun Lee ◽  
Dong-Wook Lee
Keyword(s):  
Monitoring System ◽  
Calibration Method ◽  
Similarity Score ◽  
Automatic Calibration ◽  
Online Calibration ◽  
Hough Space ◽  
Additional Equipment ◽  
Calibration Methods ◽  
Vehicle Information ◽  
Automatic Camera Calibration

We propose an automatic camera calibration method for a side-rear-view monitoring system in natural driving environments. The proposed method assumes that the camera is always located near the surface of the vehicle so that it always shoots a part of the vehicle. This method utilizes photographed vehicle information because the captured vehicle always appears stationary in the image, regardless of the surrounding environment. The proposed algorithm detects the vehicle from the image and computes the similarity score between the detected vehicle and the previously stored vehicle model. Conventional online calibration methods use additional equipment or operate only in specific driving environments. On the contrary, the proposed method is advantageous because it can automatically calibrate camera-based monitoring systems in any driving environment without using additional equipment. The calibration range of the automatic calibration method was verified through simulations and evaluated both quantitatively and qualitatively through actual driving experiments.

A Self-Calibration Method for Robotic Measurement System

1999 ◽  
Vol 122 (1) ◽  
pp. 174-181 ◽  
Author(s):  
Chunhe Gong ◽  
Jingxia Yuan ◽  
Jun Ni
Keyword(s):  
Coordinate System ◽  
Measurement System ◽  
Calibration Method ◽  
Position Measurement ◽  
Robot Calibration ◽  
Robot System ◽  
Self Calibration ◽  
World Coordinate System ◽  
Robot Accuracy ◽  
Calibration Methods

Robot calibration plays an increasingly important role in manufacturing. For robot calibration on the manufacturing floor, it is desirable that the calibration technique be easy and convenient to implement. This paper presents a new self-calibration method to calibrate and compensate for robot system kinematic errors. Compared with the traditional calibration methods, this calibration method has several unique features. First, it is not necessary to apply an external measurement system to measure the robot end-effector position for the purpose of kinematic identification since the robot measurement system has a sensor as its integral part. Second, this self-calibration is based on distance measurement rather than absolute position measurement for kinematic identification; therefore the calibration of the transformation from the world coordinate system to the robot base coordinate system, known as base calibration, is not necessary. These features not only greatly facilitate the robot system calibration, but also shorten the error propagation chain, therefore, increase the accuracy of parameter estimation. An integrated calibration system is designed to validate the effectiveness of this calibration method. Experimental results show that after calibration there is a significant improvement of robot accuracy over a typical robot workspace. [S1087-1357(00)01301-0]

scholarly journals HYBRID ONLINE MOBILE LASER SCANNER CALIBRATION THROUGH IMAGE ALIGNMENT BY MUTUAL INFORMATION

2016 ◽  
Vol III-1 ◽  
pp. 25-31 ◽  
Author(s):  
Mourad Miled ◽  
Bahman Soheilian ◽  
Emmanuel Habets ◽  
Bruno Vallet
Keyword(s):  
Mutual Information ◽  
Imaging System ◽  
Laser Scanner ◽  
Point Clouds ◽  
Calibration Method ◽  
Online Calibration ◽  
Calibration Methods ◽  
Laser Calibration ◽  
Scanner Calibration

This paper proposes an hybrid online calibration method for a laser scanner mounted on a mobile platform also equipped with an imaging system. The method relies on finding the calibration parameters that best align the acquired points cloud to the images. The quality of this intermodal alignment is measured by Mutual information between image luminance and points reflectance. The main advantage and motivation is ensuring pixel accurate alignment of images and point clouds acquired simultaneously, but it is also much more flexible than traditional laser calibration methods.

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