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Fiji Battery Defect Detection System Features

The detection of defects particularly motivates the optimization and development of innovative characterization methods, with simultaneous testing of multiple …

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Multi-Cell Testing Topologies for Defect Detection Using ...

The detection of defects particularly motivates the optimization and development of innovative characterization methods, with simultaneous testing of multiple …

Detecting the foreign matter defect in lithium-ion batteries based on battery …

The first known application of the data-driven algorithms to solve the foreign matter defect detection problem. • Experiments are conducted with implanted foreign matter defect on battery pilot manufacturing line. • …

Multi-Cell Testing Topologies for Defect Detection Using ...

Given the increasing use of lithium-ion batteries, which is driven in particular by electromobility, the characterization of cells in production and application plays a decisive role in quality assurance. The detection of defects particularly motivates the optimization and development of innovative characterization methods, with simultaneous testing of …

Surface Defects Detection and Identification of Lithium Battery …

The experimental results show that the proposed method in this paper can effectively detect surface multiple types defects of lithium battery pole piece, and the …

Autonomous Visual Detection of Defects from Battery Electrode ...

The ability of the quality assurance (QA) system developed herein to detect mechanical defects in real time is validated by an exemplary integration of the …

Deep CNN-based visual defect detection: Survey of current literature

2.1. Traditional automatic optical inspection methods Traditional AOI technique includes four steps, namely, (a) data acquisition, (b) pre-processing, (c) feature extraction, and (d) defect detection. The first step, data acquisition, is …

Energies | Free Full-Text | A Review on the Fault and Defect Diagnosis of Lithium-Ion Battery …

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 …

Sensors | Free Full-Text | Metal Surface Defect Detection Based on a Transformer with Multi-Scale Mask Feature …

Problems in defect detection include difficulties in collecting defect samples, weak network feature extraction abilities, and low training accuracies. We propose a semi-supervised anomaly detection method based on image reconstruction with a pruned–merged generative adversarial network using Transformer-based multi-scale …

Automated surface defect detection framework using machine …

The augmentation of feature extraction and transfer learning approaches with a basic deep learning algorithm, e.g., CNN, enables an efficient vision-based automated defect detection system. The present work proposes developing a classification model for detecting lateral surface defects for tapered rollers manufactured using pre-trained CNN.

An end-to-end Lithium Battery Defect Detection Method Based on ...

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 …

YOLO-v1 to YOLO-v8, the Rise of YOLO and Its Complementary Nature toward Digital Manufacturing and Industrial Defect Detection

Since its inception in 2015, the YOLO (You Only Look Once) variant of object detectors has rapidly grown, with the latest release of YOLO-v8 in January 2023. YOLO variants are underpinned by the principle of real-time and high-classification performance, based on limited but efficient computational parameters. This principle has …

Sensors | Free Full-Text | Photometric-Stereo-Based …

Automated inspection technology based on computer vision is now widely used in the manufacturing industry with high speed and accuracy. However, metal parts always appear in high gloss or shadow …

Surface defect detection of industrial components based on vision …

Surface defect detection of industrial components based on ...

Autonomous Visual Detection of Defects from Battery Electrode ...

The architecture of YOLO [] is based on a) model backbone, b) model neck, and c) model head. a) Model backbone extracts the important features from the given input image. YOLOv5 [] uses CSPNet (Cross Stage Partial Networks) as a backbone. b) Model neck generates the feature pyramids which helps the model to identify the unseen …

Battery defect detection for real world vehicles based on …

A significant amount of research has been conducted on fault diagnosis for battery systems. There are three main categories of fault diagnosis methods: knowledge …

Review A review of automated solar photovoltaic defect detection systems…

In this paper, data analysis methods for solar cell defect detection are categorised into two forms: 1) IBTs, which depend on analysing the deviations of optical properties, thermal patterns, or other visual features in images, and 2) ETTs, which depend on comparing ...

An end-to-end Lithium Battery Defect Detection Method Based on ...

Rather than the noise information on the image, so as to improve the detection ability of lithium battery surface defects. 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 battery defect data set

Resolving data imbalance in alkaline battery defect detection: a …

DOI: 10.1784/insi.2024.66.5.305 Corpus ID: 269679222 Resolving data imbalance in alkaline battery defect detection: a voting-based deep learning approach @article{Xu2024ResolvingDI, title={Resolving data imbalance in alkaline battery defect detection: a voting-based deep learning approach}, author={Zhenying Xu and Bangguo …

Review of vision-based defect detection research and its …

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 ...

Rechargeable lithium-ion cell state of charge and …

Batteries are a crucial enabling technology in many important energy solutions and they are integral to advances in portable electronics, electric vehicles, and grid storage. Continued demand for ...

Sensors | Free Full-Text | Automated Battery Making Fault Classification Using Over-Sampled Image Data CNN Features …

Due to the tremendous expectations placed on batteries to produce a reliable and secure product, fault detection has become a critical part of the manufacturing process. Manually, it takes much labor and effort to test each battery individually for manufacturing faults including burning, welding that is too high, missing welds, shifting, …

Realistic fault detection of li-ion battery via dynamical deep …

Here, we develop a realistic deep-learning framework for electric vehicle (EV) LiB anomaly detection. It features a dynamical autoencoder tailored for dynamical …

Fault Diagnosis and Detection for Battery System in Real-World Electric Vehicles Based on Long-Term Feature …

Accurate detection and diagnosis battery faults are increasingly important to guarantee safety and reliability of battery systems. Developed methods for battery early fault diagnosis concentrate on short-term data to analyze the deviation of external features without considering the long-term latent period of faults. This work proposes a novel data …

3D Point Cloud-Based Lithium Battery Surface Defects Detection …

Zong, Y., et al.: An intelligent and automated 3D surface defect detection system for quantitative 3D estimation and feature classification of material surface defects. ... X., Li, L., Li, J., Wen, C.: Surface defects detection and identification of lithium battery pole piece based on multi-feature fusion and PSO-SVM. IEEE Access 9, 85232 ...

Research papers Battery defect detection for real world vehicles …

Considering the influence of soc. on battery characteristics, we propose a AIEM-SOC to dynamically extract the effective soc. interval for battery defect detection. (2) GDP-DLCSS is proposed for battery defect detection, the parameters of which are driven by data to avoid the subjectivity of manually defined thresholds.

Realistic fault detection of li-ion battery via dynamical deep learning

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). To facilitate model ...

A Review on the Fault and Defect Diagnosis of Lithium-Ion Battery …

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 …

Materials | Free Full-Text | Using Deep Learning to Detect Defects …

The detection of product defects is essential in quality control in manufacturing. This study surveys stateoftheart deep-learning methods in defect detection. First, we classify the defects of products, such as electronic components, pipes, welded parts, and textile materials, into categories. Second, recent mainstream techniques and …

Electronics | Free Full-Text | A YOLOv8-Based Approach for Real-Time Lithium-Ion Battery Electrode Defect Detection …

A YOLOv8-Based Approach for Real-Time Lithium-Ion ...

Fault Diagnosis and Detection for Battery System in Real-World …

Accurate detection and diagnosis battery faults are increasingly important to guarantee safety and reliability of battery systems. Developed methods for battery …

Coatings | Free Full-Text | Steel Surface Defect Recognition: A …

Steel Surface Defect Recognition: A Survey

Sensors | Free Full-Text | Visual-Based Defect …

This paper reviews automated visual-based defect detection approaches applicable to various materials, such as metals, ceramics and textiles. In the first part of the paper, we present a general …

Nondestructive Defect Detection in Battery Pouch Cells: A …

The identification and location of critical defects inside battery cells before the performance decreases or safety issues arise remain a challenge. This study compares two nondestructive testing methods for the 3D visualization of defects at different depths inside a …