Systematic overview of (a) the machine vision-based PCB defect detection methods and their common performance evaluation indicators, (b) public datasets for evaluating machine vision-based PCB defect inspection system, and (c) the feedback mechanism and optimization process at the inspection system and manufacturing …
Systematic overview of (a) the machine vision-based PCB defect detection methods and their common performance evaluation indicators, (b) public datasets for evaluating machine vision-based PCB defect inspection system, and (c) the feedback mechanism and optimization process at the inspection system and manufacturing …
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 …
Research on detection algorithm of lithium battery surface defects based on embedded machine vision ... use Hough detection method to locate the battery surface, and design the battery defect algorithm for this, and compare the algorithm through experiments. ... Journal of Intelligent & Fuzzy Systems, vol. 41, no. 3, pp. 4327-4335, 2021 ...
The invention provides a method and a system for detecting appearance defects of a battery module based on deep learning, wherein the method comprises the following steps: obtaining appearance defect sample data of the battery module, extracting data characteristics of the appearance defect sample data, and performing category labeling …
Hundreds of electric vehicle (EV) battery thermal runaway accidents resulting from untreated defects restrict further development of EV industry. 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, …
GDP-DLCSS is proposed for battery defect detection, the parameters of which are driven by data to avoid the subjectivity of manually defined thresholds. (3) The …
The global market research firm QYResearch forecasts that the global market for lithium-ion battery lead taps will grow at an average annual rate of 8.1% from USD 75.6 billion in 2022 to 1.33 billion by 2029 [] addition, the growth of the EV market is expected to accelerate from 2023 due to increasing EV purchase subsidies under the …
During the manufacturing of lithium-ion battery electrodes, it is difficult to prevent certain types of defects, which affect the overall battery performance and lifespan. Deep learning computer vision methods were used to evaluate the quality of lithium-ion battery electrode for automated detection of microstructural defects from light …
2.3 Defect Detection of Battery. The defect detection of the cell mainly includes the defect values of 4 edges and 4 chamfers. Its principle is to determine the starting point and ending point of the left defect detection toolkit findline according to the two vertices of top left and bottom left. As follows: Left_Line. RunParams ...
Experiments show that AIA DETR model can well detect the defect target of lithium battery, effectively reduce the missed detection problem, and reach 81.9% AP in the lithium …
Fault Detection and Diagnosis of the Electric Motor Drive ...
DOI: 10.1007/s10845-019-01484-x Corpus ID: 201239143; Image-based defect detection in lithium-ion battery electrode using convolutional neural networks @article{Badmos2019ImagebasedDD, title={Image-based defect detection in lithium-ion battery electrode using convolutional neural networks}, author={Olatomiwa Badmos and …
2.3. Acquisition of welding area images. A CMOS digital camera (BASLER Basler acA2500-14um camera with UTRON HS2514J lens) and a white annular LED light source (OPT-RI7030) with a light intensity range of 0–255 levels were used to capture the welding area images for the laser welding AOI system shown in Fig. 4 spite of the fact …
Firstly, a density-based semi-supervised cluster method (DBSSC) is proposed containing three novelties: The objective function is originally defined and a …
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.
1 Introduction. The improvement of quality assurance in the production of lithium-ion battery cells is of major importance for the further development of the electromobility market and its various applications as well as for the deployment of stationary battery storage systems as a key enabler for a successful energy transition.
The defect detection methodologies for lithium battery electrode plates predominantly fall into two categories: traditional defect detection algorithms and those …
Turbine detection system: Function: The defect of the shallow surface of metal parts is detected through the analysis and treatment of the eddy current. It is suitable for defect detection of conductive materials. Trait: Eddy current testing is only applicable to conductive materials. It can only detect defects on the surface or near the ...
A voting-based recognition algorithm containing three parts designed to provide fine-grained category representations for alkaline battery defect detection and a voting-based prediction approach is proposed to improve accuracy and obtain the final results. Alkaline battery defect detection is crucial for ensuring product quality and …
Improve the accuracy of polar defect detection, and use the CIoU loss function to replace the GIoU function, so that the regression process focuses more on high-quality anchor frames and improves the convergence speed, regression accuracy, and robustness of the model. In order to meet the needs of the detection accuracy and speed …
The 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 …
Surface Defect Detection Methods for Industrial Products
The supporting components and system that form the BOP for a BESS consists of a fire detection and suppression system, a power distribution set-up and a thermal management system. A BESS is inherently vulnerable to defects originating from all upstream components and this is attested by the large number of direct findings in the …
Dingming Yang et al. [23] proposed an improved pipeline weld defect detection algorithm for YOLOv5, which effectively improved the detection efficiency and basically met the accuracy and speed requirements for defect detection in the industry. Although the above methods have basically achieved defect detection in the industry, …
1. Introduction. Electric vehicles (EVs) have been widely recognized as an integral part of efficient and green transportation. Battery systems are a key component of EVs that largely defines their performance and cost-effectiveness [1], [2], [3].With the eye-catching development of advanced lithium-ion batteries, they have been established as …
Download figure: Standard image High-resolution image Therefore, defects detection is necessary before the use of thermal batteries. Traditional detection methods mainly focus on electrochemical performance testing or detection of the structure and …
High-power semiconductor lasers play a crucial role in optical communication systems, and their reliability is key to the normal operation of the system. Catastrophic Optical Damage generated during operation is a major factor affecting chip performance and lifetime. Accurate detection of the location and development process of …
Challenges in real-world EV battery fault detection. Real-world anomaly detection models can only make use of observational data from existing battery management systems (BMSs).
The DETR model is often affected by noise information such as complex backgrounds in the application of defect detection tasks, resulting in detection of some targets is ignored. In this paper, 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 …
With 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 …