Aiming at the characteristics of the periodic stacking structure of a lithium-ion battery core and the corresponding relationship between the air-coupled ultrasonic transmission initial wave and the wave propagation mode in each layer medium of a lithium-ion battery, the homogenized finite element model of a lithium-ion battery was …
About Photovoltaic Energy StorageDefect detection of lithium batteries is a crucial step in lithium battery production. However, traditional detection methods mainly rely on the human eyes to observe the bottom defects of lithium ...
About Photovoltaic Energy StorageIn response to the problems of low efficiency and low accuracy of the traditional manual method of detecting defects in lithium battery poles. In this paper, we propose a way to detect the defects of lithium battery poles based on the combination of mean shift and gray-level co-occurrence matrix (GLCM). Firstly, ROI extraction of the coated area of the …
About Photovoltaic Energy StorageCompared with the traditional detection technology, the defect detection of lithium-ion battery using industrial CT detection technology has many advantages, including component measurement of complex battery internal structure through high-density information in a non-contact and non-destructive manner. This paper introduces a …
About Photovoltaic Energy StorageWith the continuous development of science and technology, cylindrical lithium batteries, as new energy batteries, are widely used in many fields. In the production process of lithium batteries, various defects may occur. To detect the defects of lithium batteries, a detection algorithm based on convolutional neural networks is …
About Photovoltaic Energy StorageA YOLOv8-Based Approach for Real-Time Lithium-Ion ...
About Photovoltaic Energy StorageAccurate 3D representations of lithium-ion battery electrodes can help in understanding and ultimately improving battery performance. Here, the authors report a methodology for using deep-learning ...
About Photovoltaic Energy StorageState of the Art in Defect Detection Based on Machine Vision
About Photovoltaic Energy StorageDeep-Learning-Based Lithium Battery Defect Detection via ...
About Photovoltaic Energy StorageSurface defect detection of cylindrical lithium-ion battery by ...
About Photovoltaic Energy StorageData-driven intelligent detection methods have been widely used in the detection of defects in lithium batteries, with outstanding results. However, there are situations of inaccurate labeling due to category similarity in the labeling process, resulting in noisy labels that subsequently influence the model''s prediction. To solve this problem, we propose a …
About Photovoltaic Energy StorageIn order to reduce the cost of lithium-ion batteries, production scrap has to be minimized. The reliable detection of electrode defects allows for a quality control and fast operator reaction in ideal closed control loops and a well-founded decision regarding whether a piece of electrode is scrap. A widely used inline system for defect detection is …
About Photovoltaic Energy StorageAbstract: In the domain of fold defect detection in lithium batteries, gathering a sufficient number of defect samples for training deep learning models is often challenging due to …
About Photovoltaic Energy StorageHere the authors utilize the measurement of tiny magnetic field changes within a cell to assess the lithiation state of the active material, and detect defects.
About Photovoltaic Energy StorageProgress and challenges in ultrasonic technology for state ...
About Photovoltaic Energy StorageThe results show that the optimization algorithm can improve the accuracy and speed of the lithium battery and achieves a 92.7% detection accuracy, surpassing the original network by 2.1%. For the traditional algorithm to detect lithium battery defects, the missing rate is high and the speed is slow, an improved YOLOv7 algorithm was proposed.
About Photovoltaic Energy StorageDue to the inability to directly measure the internal state of batteries, there are technical challenges in battery state estimation, defect detection, and fault …
About Photovoltaic Energy StorageLaser welding is widely used in lithium-ion batteries and manufacturing companies due to its high energy density and capability to join different materials. Welding quality plays a vital role in the durability and effectiveness of welding structures. ... different instruments and methods are needed for laser welding defect detection. In most ...
About Photovoltaic Energy StorageThirdly, it outlines the current status, main technological approaches, and challenges of ultrasonic technology in battery defect and fault diagnosis, including defect detection, lithium plating, gassing, battery wetting, and thermal runaway early warning, revealing the diversity and potential applicability of ultrasonics in battery research.
About Photovoltaic Energy StorageHere, authors present a large-scale electric vehicle charging dataset for benchmarking existing algorithms, and develop a deep learning algorithm for detecting …
About Photovoltaic Energy StorageDeep learning computer vision methods were used to evaluate the quality of lithium-ion battery electrode for automated detection of microstructural defects from light microscopy images of the sectioned cells, demonstrating that deep learning models are able to learn accurate representations of the microstructure images well enough to distinguish …
About Photovoltaic Energy Storage1. Introduction. Complying with the goal of carbon neutrality, lithium-ion batteries (LIBs) stand out from other energy storage systems for their high energy density, high power density, and long lifespan [1], [2], [3].Nevertheless, batteries are vulnerable under abuse conditions, such as mechanical abuse, electrical abuse, and thermal abuse, …
About Photovoltaic Energy StorageIn this work, a few-shot learning approach for 3D defect detection in lithium batteries is proposed. The multi-exposure-based structured light method is introduced to reconstruct the 3D shape of the lithium battery. Then, the anomaly part of the 3D point cloud is transferred into 2D images by the height-gray transformation.
About Photovoltaic Energy StorageTargeting the issue that the traditional target detection method has a high missing rate of minor target defects in the lithium battery electrode defect detection, …
About Photovoltaic Energy StorageIn 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 ...
About Photovoltaic Energy StorageThe battery system, as the core energy storage device of new energy vehicles, faces increasing safety issues and threats. An accurate and robust fault diagnosis technique is crucial to guarantee the safe, reliable, and robust operation of lithium-ion batteries. However, in battery systems, various faults are difficult to diagnose and isolate …
About Photovoltaic Energy StorageFor the traditional algorithm to detect lithium battery defects, the missing rate is high and the speed is slow, an improved YOLOv7 algorithm was proposed. Firstly, CBAM attention mechanism is added to feature extraction part, which can enhance network''s representation ability. Secondly, in the feature fusion part, ConvNeXt …
About Photovoltaic Energy StorageKeywords: lithium-ion battery, ultrasonic, non-destructive testing, material property, battery defect, battery safety. Citation: Yi M, Jiang F, Lu L, Hou S, Ren J, Han X and Huang L (2021) Ultrasonic Tomography Study of Metal Defect Detection in Lithium-Ion Battery. Front. Energy Res. 9:806929. doi: 10.3389/fenrg.2021.806929
About Photovoltaic Energy StorageTargeting the issue that the traditional target detection method has a high missing rate of minor target defects in the lithium battery electrode defect detection, this paper proposes an improved and optimized battery electrode defect detection model based on YOLOv8. Firstly, the lightweight GhostCony is used to replace the standard …
About Photovoltaic Energy StorageAbstract: This research addresses the critical challenge of classifying surface defects in lithium electronic components, crucial for ensuring the reliability and safety of lithium …
About Photovoltaic Energy StorageIn order to reduce the cost of lithium-ion batteries, production scrap has to be minimized. The reliable detection of electrode defects allows for a quality control and fast operator reaction in ideal …
About Photovoltaic Energy StorageA novel approach for surface defect detection of lithium ...
About Photovoltaic Energy StorageThe first known application of the data-driven algorithms to solve the foreign matter defect detection problem. • Experiments are conducted with implanted foreign …
About Photovoltaic Energy StorageAIA DETR model is proposed by adding AIA (attention in attention) module into transformer encoder part, which makes the model pay more attention to correct defect information so as to improve the detection ability of lithium battery surface defects. The DETR model is often affected by noise information such as complex backgrounds in the …
About Photovoltaic Energy StorageWith the continuous development of science and technology, cylindrical lithium batteries, as new energy batteries, are widely used in many fields. In the production process of lithium batteries, various defects may occur. To detect the defects of lithium batteries, a detection algorithm based on convolutional neural networks is proposed in this paper. …
About Photovoltaic Energy StorageThe multi-exposure-based structured light method is introduced to reconstruct the 3D shape of the lithium battery using the MiniImageNet datasets as the source domain to pretrain the Cross-Domain Few-Shot Learning (CD-FSL) model. Detecting the surface defects in a lithium battery with an aluminium/steel shell is a difficult task. The effect of reflectivity, …
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