Fast Calibration Method of Large Dimension Measurement System Based on Multi-Camera Array

2018 ◽  
Vol 38 (12) ◽  
pp. 1215002 ◽  
Author(s):  
吴庆华 Wu Qinghua ◽  
陈慧 Chen Hui ◽  
朱思斯 Zhu Sisi ◽  
周阳 Zhou Yang ◽  
万偲 Wan Cai
1999 ◽  
Author(s):  
Chunhe Gong ◽  
Jingxia Yuan ◽  
Jun Ni

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.


2019 ◽  
Vol 39 (6) ◽  
pp. 0612003
Author(s):  
马冬晓 Dongxiao Ma ◽  
汪家春 Jiachun Wang ◽  
陈宗胜 Zongsheng Chen ◽  
王冰 Bing Wang ◽  
刘洋 Yang Liu

2019 ◽  
Vol 46 (1) ◽  
pp. 0104003
Author(s):  
马国庆 Ma Guoqing ◽  
刘丽 Liu Li ◽  
于正林 Yu Zhenglin ◽  
曹国华 Cao Guohua ◽  
王强 Wang Qiang

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 869 ◽  
Author(s):  
Tianxiang Xu ◽  
Zhipeng Chen ◽  
Zhaohui Jiang ◽  
Jiancai Huang ◽  
Weihua Gui

Capturing the three-dimensional (3D) shape of the burden surface of a blast furnace (BF) in real-time with high accuracy is crucial for improving gas flow distribution, optimizing coke operation, and stabilizing BF operation. However, it is difficult to perform 3D shape measurement of the burden surface in real-time during the ironmaking process because of the high-temperature, high-dust, and lightless enclosed environment inside the BF. To solve this problem, a real-time 3D measurement system is developed in this study by combining an industrial endoscope with a virtual multi-head camera array 3D reconstruction method. First, images of the original burden surface are captured using a purpose-built industrial endoscope. Second, a novel micro-pixel luminance polarization method is proposed and applied to compensate for the heavy noise in the backlit images due to high dust levels and poor light in the enclosed environment. Third, to extract depth information, a multifeature-based depth key frame classifier is designed to filter out images with high levels of clarity and displacement. Finally, a 3D shape burden surface reconstruction method based on a virtual multi-head camera array is proposed for capturing the real-time 3D shape of the burden surface in an operational BF. The results of an industrial experiment illustrate that the proposed method can measure the 3D shape of the entire burden surface and provide reliable burden surface shape information for BF control.


2008 ◽  
Vol 392-394 ◽  
pp. 435-438
Author(s):  
Hua Guo ◽  
L. Bai ◽  
J. Liu ◽  
Y. Shi

This paper adopted the photoelectric micro measurement system based on CCD which was independently developed by Laboratory of Process Automatic and Detection Harbin Institute of Technology to detect dimension of the small precise parts. Under the various focusing status, it was discovered that articulation of focusing has huge effect on the measurement of measurand. According to the characteristics of measurand, we adopted the entropy function as the evaluation function of automatic focusing, developed a special software to process entropy value of the picked images, and obtained the relationship of focusing evaluation function and measurement error through a large number of experiments. The experimental result effectively verified the effect of articulation of focusing on dimension measurement.


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