AIA 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 …
Thermal Battery Multi-Defects Detection and Discharge Performance Analysis Based on Computed Tomography Imaging, Dalong Tan, Hong Zhang, …
As an essential component of the new energy vehicle battery, current collectors affect the performance of battery and are crucial to the safety of passengers. The significant differences in shape and scale among defect types make it challenging for the model detection of current collector defects. In order to reduce application costs and …
The defect detection method based on the object detection network has attracted more and more attention, which can obtain more sufficient defect information and can not only identify whether there are defects in the current image but also accurately locate the location and size of the defects, to further visualize the defects and analyze …
Flat panel CT detection is based on the principle of projection amplification, resulting in a decrease in sample resolution as its size increases. 25 To enhance image resolution, two common approaches are reducing x-ray focus and/or employing a higher resolution flat-panel detector. 26 However, these methods do not …
DOI: 10.1117/12.2615289 Corpus ID: 244452083; Lithium battery surface defect detection based on the YOLOv3 detection algorithm @inproceedings{Lang2021LithiumBS, title={Lithium battery surface defect detection based on the YOLOv3 detection algorithm}, author={Xianli Lang and Yu Zhang and Shuangbao …
Abstract: In order to realize the automatic detection of surface defects of lithium battery pole piece, a method for detection and identification of surface defects of lithium battery pole piece based on multi-feature fusion and PSO-SVM was proposed in this paper. Firstly, image subtraction and contrast adjustment were used to preprocess the …
Terahertz waves offer advantages for nondestructive detection of hidden objects/defects in materials, as they can penetrate most optically-opaque materials. However, existing terahertz inspection ...
In contrast to the existing battery diagnosis and fault detection methods that use battery operating data as input, we conducted the experiments and implanted …
Battery defect detection based on the abnormality of external parameters is a promising way to reduce this kind of thermal runaway accidents and protect EV consumers from fire danger. However, the influence of temperature and EV …
In 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 …
In addition, the current power battery defect detection is mostly based on equipment testing after production and recall, which does not make good use of actual data [37]. To this end, this paper proposes a multi-layer fault diagnosis framework based on an adaptive SOC interval extraction method (AIEM-SOC) and Gaussian-distribution ...
This research addresses the critical challenge of classifying surface defects in lithium electronic components, crucial for ensuring the reliability and safety of lithium batteries. …
A YOLOv8-Based Approach for Real-Time Lithium-Ion ...
Accurate evaluation of Li-ion battery (LiB) safety conditions can reduce unexpected cell failures, facilitate battery deployment, and promote low-carbon economies.
The voltage abnormal fluctuation is a warning signal of short-circuit, over-voltage and under-voltage. This paper proposes a scheme of three-layer fault detection …
اتصل بنا