Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Preoperative Intravitreal Conbercept Facilitates Vitrectomy in Proliferative Diabetic Retinopathy: Is Attention Required for the Fellow Eye?

Journal of ophthalmology·2019
Same author

Nanotribological Properties of Ga- and N-Faced Bulk Gallium Nitride Surfaces Determined by Nanoscratch Experiments.

Materials (Basel, Switzerland)·2019
Same author

Genetic Diversity and Population Structure Analysis of Three Deep-Sea Amphipod Species from Geographically Isolated Hadal Trenches in the Pacific Ocean.

Biochemical genetics·2019
Same author

Properties and Reaction Mechanisms of Magnesium Phosphate Cement Mixed with Ferroaluminate Cement.

Materials (Basel, Switzerland)·2019
Same author

Zein Particle-Stabilized Water-In-Water Emulsion as a Vehicle for Hydrophilic Bioactive Compound Loading of Riboflavin.

Journal of agricultural and food chemistry·2019
Same author

Cerebellar Fastigial Nucleus Stimulation in a Chronic Unpredictable Mild Stress Rat Model Reduces Post-Stroke Depression by Suppressing Brain Inflammation via the microRNA-29c/TNFRSF1A Signaling Pathway.

Medical science monitor : international medical journal of experimental and clinical research·2019
Same journal

DARUMA: a gateway to fast and easy prediction of intrinsically disordered regions.

PeerJ. Computer science·2026
Same journal

Alzheimer's disease detection using a quantum deep neural network with Haralick feature extraction and simulated annealing optimization.

PeerJ. Computer science·2026
Same journal

Network anomaly detection using Deep Autoencoder and parallel Artificial Bee Colony algorithm-trained neural network.

PeerJ. Computer science·2026
Same journal

An anomaly detection model for multivariate time series with anomaly perception.

PeerJ. Computer science·2026
Same journal

Retraction: A wormhole attack detection method for tactical wireless sensor networks.

PeerJ. Computer science·2026
Same journal

Evaluation of mental disorder with prioritization of its type by utilizing the bipolar complex fuzzy decision-making approach based on Schweizer-Sklar prioritized aggregation operators.

PeerJ. Computer science·2026
查看所有相关文章

相关实验视频

Updated: Jun 5, 2025

In Situ Monitoring of the Accelerated Performance Degradation of Solar Cells and Modules: A Case Study for CuIn,GaSe2 Solar Cells
09:19

In Situ Monitoring of the Accelerated Performance Degradation of Solar Cells and Modules: A Case Study for CuIn,GaSe2 Solar Cells

Published on: October 3, 2018

8.3K

基于计算机视觉的算法用于精确检测和分类光伏模块中的缺陷.

Jian Guo1

  • 1Department of Information Engineering, Xiamen Ocean Vocational College, Xiamen, Fujian, China.

PeerJ. Computer science
|December 9, 2024
PubMed
概括
此摘要是机器生成的。

太阳能电池板的自动缺陷检测使用计算机视觉和人工智能. 这种方法精确地识别小缺陷,提高太阳能系统的可靠性和性能.

关键词:
计算机视觉 计算机视觉 计算机视觉缺陷检测 检测缺陷检测 检测缺陷检测太阳能光伏模块的使用情况渐进式注释 渐进式注释转移学习转移学习

更多相关视频

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography
11:34

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography

Published on: May 15, 2017

11.1K
Indoor Experimental Assessment of the Efficiency and Irradiance Spot of the Achromatic Doublet on Glass ADG Fresnel Lens for Concentrating Photovoltaics
09:00

Indoor Experimental Assessment of the Efficiency and Irradiance Spot of the Achromatic Doublet on Glass ADG Fresnel Lens for Concentrating Photovoltaics

Published on: October 27, 2017

8.8K

相关实验视频

Last Updated: Jun 5, 2025

In Situ Monitoring of the Accelerated Performance Degradation of Solar Cells and Modules: A Case Study for CuIn,GaSe2 Solar Cells
09:19

In Situ Monitoring of the Accelerated Performance Degradation of Solar Cells and Modules: A Case Study for CuIn,GaSe2 Solar Cells

Published on: October 3, 2018

8.3K
Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography
11:34

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography

Published on: May 15, 2017

11.1K
Indoor Experimental Assessment of the Efficiency and Irradiance Spot of the Achromatic Doublet on Glass ADG Fresnel Lens for Concentrating Photovoltaics
09:00

Indoor Experimental Assessment of the Efficiency and Irradiance Spot of the Achromatic Doublet on Glass ADG Fresnel Lens for Concentrating Photovoltaics

Published on: October 27, 2017

8.8K

科学领域:

  • 可再生能源可再生能源是可再生能源.
  • 人工智能的人工智能
  • 计算机视觉 计算机视觉

背景情况:

  • 太阳能在全球范围内至关重要,需要高质量的光伏模块.
  • 自动缺陷检测对于保持太阳能系统效率至关重要.
  • 在复杂的环境中识别小缺陷仍然是一个挑战.

研究的目的:

  • 开发一种先进的自动化系统,用于检测光伏模块的轻微缺陷.
  • 为了提高太阳能电池板检查中缺陷识别的精度和速度.
  • 提高太阳能发电系统的整体质量和运行可靠性.

主要方法:

  • 使用渐进式注释方法来准确标记缺陷样本.
  • 采用计算机视觉技术来准确细分模块和缺陷.
  • 部署了一个转移学习模型,特别是面具区域卷积神经网络 (Mask R-CNN),用于缺陷分类.

主要成果:

  • 在缺陷分类中实现了高精度 (98.7%) 和回忆 (0.913).
  • 演示了每秒280.69的快速检测速度.
  • 记录了3.53毫秒的低推断时间用于缺陷识别.

结论:

  • 开发的计算机视觉算法显著改善了轻微光伏模块缺陷的自动检测.
  • 面具R-CNN模型为太阳能电池板质量控制提供了高度准确和高效的解决方案.
  • 这一进步对于确保太阳能基础设施的可靠性和性能至关重要.