公开(公告)号：US20240150149A1

公开(公告)日：2024-05-09

申请号：US18404887

申请日：2024-01-05

Applicant: JIANGSU CONTEMPORARY AMPEREX TECHNOLOGY LIMITED

Inventor： Jinhuo Gao ,  Yu Luo ,  Shengsheng Yu ,  Houyong Li ,  Feilong Xu

IPC: B65H43/04 ,  B65H43/08 ,  G01N21/89 ,  H01M10/0587

CPC classification number: B65H43/04 ,  B65H43/08 ,  G01N21/89 ,  H01M10/0587 ,  B65H2553/40 ,  B65H2701/12 ,  G01N2201/02

Abstract: Provided are an electrode plate wrinkling detection apparatus and cell production equipment, pertaining to the field of battery technologies. The electrode plate wrinkling detection apparatus includes an image detection mechanism and a moving mechanism. The moving mechanism is configured to drive the image detection mechanism to move on a winding machine within a region directly facing a cell and adjust a shooting angle of the image detection mechanism. The image detection mechanism includes an image capture device and a detection module that are interconnected. The image capture device is configured to photograph a cell to obtain a picture of the cell and transmit the picture of the cell to the detection module. The detection module is configured to examine the picture of the cell to detect presence of electrode plate wrinkling using a grayscale algorithm and output a detection result.

公开(公告)号：US20240221150A1

公开(公告)日：2024-07-04

申请号：US18610287

申请日：2024-03-20

Applicant: JIANGSU CONTEMPORARY AMPEREX TECHNOLOGY LIMITED

Inventor： Jinhuo Gao ,  Shengsheng Yu ,  Yu Luo ,  Houyong Li ,  Feilong Xu ,  Jiyong Liu

IPC: G06T7/00 ,  G06V10/764 ,  G06V10/776 ,  G06V10/82

CPC classification number: G06T7/001 ,  G06V10/764 ,  G06V10/776 ,  G06V10/82 ,  G06T2207/20081 ,  G06T2207/30136

Abstract: Provided are an electrode plate wrinkling detection method and system, a terminal, and a storage medium. The electrode plate wrinkling detection method includes: acquiring images of cells with wrinkled electrode plates and images of cells with non-wrinkled electrode plates; performing type labeling processing on the acquired images and constructing a database by using the labeled images; based on the database, training via a convolutional neural network to generate an electrode plate wrinkling detection model; testing and calibrating the electrode plate wrinkling detection model by using images outside the database; and performing electrode plate wrinkling detection on cell images obtained in a real-time manner during a battery winding process by using the tested and calibrated electrode plate wrinkling detection model.