Weld defect detection of power battery pack based on image segmentation. (8th October 2022)

• Record Type: Journal Article
• Authors: Tao, Bo; He, Fuqiang; Tang, Quan; Guo, Zhinan; Long, Hansen; Li, Shidong; Cao, Yongcheng; Ruan, Guijian
• Is Part Of: International journal of wireless and mobile computing. Volume 23:Number 2(2022)
• Page Start: 139
• Page End: 145
• Publication Date: 2022-10-08
• Subjects: power battery -- line laser sensor -- threshold segmentation -- connected domain -- defect classification; Mobile computing -- Periodicals; Wireless communication systems -- Periodicals; 004.6
• Languages: English
• ISSNs: 1741-1084

Abstract

The safety and production efficiency are an important part of the power batteries production process and need to be considered seriously. Aiming at the welding quality of a power battery, a three-dimensional detection method based on the line laser sensor was proposed. Firstly, the depth data of the weld surface of the battery top cover is obtained by using a line laser sensor, and the defect area is segmented by using a multi thresholds segmentation method based on contour lines. Through the connected domain algorithm, the centres of defective areas are located. And the defect type is determined according to distance between the centres of the defect areas. Experimental results show that the detection rate reaches 97%, which indicates that the scheme has high detection accuracy and strong stability, and verifies the effectiveness of the method.