Research on Visual Detection Algorithm of 500kV High Voltage Live Operating Robot

Abstract The 500kV transmission line is exposed to the outdoor for a long time. It is affected by complex climate charge change and other factors which leads to line connection parts bolt loosening, wire breaking and fixture damage and other line failures. In order to ensure the stable transmission of electric energy, power operators need to wear shielding suits and work in the high-risk and high-voltage environment. Use of electric power operation robot instead of manual operation is an effective way to liberate maintenance staff labor. But robots still have some problems such as low degree of automation and low efficiency of power operation. Machine vision detection technology in recent years has been widely used in major areas including deep learning as emerging visual detection technology shows excellent performance. In this paper, the vision detection algorithm is studied respectively for the bolt fastening end working device and wire repairing end working device of the live transmission line robot to improve the operating efficiency of the robot.

Download Full-text

Research on detection algorithm of lithium battery surface defects based on embedded machine vision

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189693 ◽

2021 ◽

pp. 1-9

Author(s):

Yonggang Chen ◽

Yufeng Shu ◽

Xiaomian Li ◽

Changwei Xiong ◽

Shenyi Cao ◽

...

Keyword(s):

Lithium Battery ◽

Surface Defects ◽

Visual Detection ◽

Rapid Development ◽

Detection Algorithm ◽

Large Error ◽

Detection Algorithms ◽

Manual Inspection ◽

Low Efficiency ◽

Vision Detection

In the production process of lithium battery, the quality inspection requirements of lithium battery are very high. At present, most of the work is done manually. Aiming at the problem of large manual inspection workload and large error, the robot visual inspection technology is applied to the production of lithium battery. In recent years, with the rapid development and progress of science and technology, the rapid development of visual detection hardware and algorithms, making it possible to screen defective products through visual detection algorithms. This paper takes lithium battery as the research object, and studies its vision detection algorithm. As a common commodity, the quality of lithium battery is the key for users to choose. With the increasing requirements of users for battery quality, how to produce high-quality battery is the key problem to be solved by manufacturers. However, at present, the defects of battery surface are mostly carried out manually. There are low efficiency and low detection rate in the process of manual detection. In this paper, the visual detection algorithm is studied to detect the defects such as pits, rust marks and broken skin on the surface of lithium battery, specifically to design the imaging experimental platform of lithium battery; use different lighting schemes to design different battery positioning and extraction algorithms; use Hough detection method to locate the battery surface, and design the battery defect algorithm for this, and compare the algorithm through experiments.

Download Full-text

Transmission Line Insulators Detection Based on KAZE Algorithm

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.936.2184 ◽

2014 ◽

Vol 936 ◽

pp. 2184-2189

Author(s):

Dan Li ◽

Meng Zhang ◽

Zu Bing Tong

Keyword(s):

Transmission Line ◽

Nearest Neighbor ◽

Scale Space ◽

Detection Algorithm ◽

Obstacle Detection ◽

Feature Vectors ◽

Inspection Robot ◽

Detection Technology ◽

Matching Criteria ◽

Nonlinear Scale

Transmission Line obstacle detection technology is one of the hot spots of computer vision and transmission line inspection robot system.As the most common obstacle of inspection robot,correctly identify of insulators can help improve the reliability and accuracy of self-inspection. Low robustness of traditional detection algorithm can not meet the requirements on insulators detection when dealing with complex environment. To solve the above problem, a transmission line insulators detection method based on KAZE algorithm is given. The feature extraction is done in the nonlinear scale space, and feature vectors are formed with M-SURF algorithm, what’s more, feature vectors detecting is worked through the nearest neighbor algorithm as matching criteria and RANSC generated algorithm. Experimental results show that the effect of insulators detection algorithm based on KAZE detect faster and also make a good performance on accuracy and robustness.

Download Full-text