Cell abnormality detection method and system for laminated battery
An abnormality detection and cell technology, applied in measurement devices, photovoltaic power generation, instruments, etc., can solve the problems of low accuracy, missed detection, long detection time, etc., to avoid missed detection, improve computing efficiency, and improve recognition accuracy. Effect
Active Publication Date: 2022-08-09
浙江双元科技股份有限公司
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[0005] This method can safely detect the internal structure of the lithium battery through the X-Ray visual system, but the detection time is long, and when the situation is more complicated, the detection accuracy is low, and there are missed detections
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[0060] In order to better understand the above technical solutions, the above technical solutions will be described in detail below with reference to the accompanying drawings and specific embodiments.
[0061] In order to facilitate the understanding of the present application, the structure of the laminated battery cell involved in the present application is first described. refer to figure 1 , the cell of the laminated battery includes a plurality of positive electrode sheets 1001 and negative electrode sheets 1002 arranged at intervals. 1002 leads out a negative tab 1005. A separator is provided between the positive electrode sheet 1001 and the negative electrode sheet 1002, and lithium ions in the electrolyte in the separator move to generate electricity. A single-sided sheet 1003 is arranged between every two cells to distinguish two or more cells.
[0062] The technical solutions of the embodiments of the present application are described in detail below with referen...
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The invention discloses a cell abnormality detection method and system for a laminated battery. The method includes: collecting an image of a cell to be inspected through X-Ray equipment; preprocessing the image of the cell to be inspected to extract an image of a region of interest; The region of interest image is input to the pre-established neural network detection model to obtain the number of layers of positive and negative plates in the region of interest image; the region of interest image is segmented according to the number of layers to obtain a segmented image; the segmented image is input to The pre-established convolutional neural network model is used to obtain the heatmap of the endpoints of the positive electrode and the end of the negative electrode in each segmented image; screen the endpoints of the positive electrode and the end of the negative electrode in the heatmap of the end of the positive electrode and the end of the negative electrode; Anomaly detection is carried out based on the screened positive and negative plate endpoints; this method calculates the number of pole plate layers through a neural network, and uses a convolutional neural network model for feature recognition, with high anomaly detection accuracy and high efficiency.
Description
technical field [0001] The invention relates to the technical field of battery cell detection, in particular to a method and system for abnormality detection of a battery cell of a laminated battery. Background technique [0002] The method of non-destructive testing of laminated lithium-ion batteries using X-ray imaging technology has become an indispensable link in production, which is helpful for battery quality control. When X-rays are used to detect the abnormality of lithium electronic cells, X-rays are first sent out through the X-Ray transmitter to penetrate the cells, and then the X-rays are received and imaged by the receiving end, and then the X-ray images are processed by software algorithms to obtain relevant data. , and finally determine the good and bad products according to the process requirements. In the testing process, automated mechanical equipment is mainly responsible for the logistics and transportation of cells or batteries composed of cells, photo ...
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IPC IPC(8): G06T7/00G06V10/25G06V10/26G06V10/82G06N3/04G01N23/04
CPCG06T7/0004G01N23/04G01N2223/401G01N2223/1016G06N3/045Y02P70/50
Inventor 陈文君唐玉辉胡美琴
Owner 浙江双元科技股份有限公司