首页|基于图像识别的水电站漏液检测模型研究

基于图像识别的水电站漏液检测模型研究

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提出了基于融合电站高清摄像头和视频数据的方法,通过研究图像识别的深度学习框架、视频面向视频序列的动态目标识别技术研究和增强设备目标集合形变的识别能力研究,建立设备图像样本库,实现水电站设备漏液缺陷的智能识别.通过识别模型研究成果,验证了适用于水电站场景的识别模型特点和技术要求,为今后视频识别技术在水电站应用推广提供了重要参考.
Research on Leakage Detection Model of Hydropower Station Based on Image Recognition
A method based on the fusion of high-definition camera and video data from power stations is proposed to establish a sample library of equipment images to realize the intelligent recognition of leakage defects in hydropower station equipment through the study of the deep learning framework of image recognition,the study of video-oriented dynamic target recognition technology for video sequences and the study of the recognition ability to enhance the deformation of the collection of equipment targets.Through the recognition model research results,the characteristics and technical requirements of the recognition model applicable to hydropower station scenarios are verified,which provides an important reference for the promotion of future application of video recognition technology in hydropower stations.

visual recognitionliquid leakage detectionmodeling

吴海涛

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四川明星电力股份有限公司,四川 遂宁6210000

视觉识别 漏液检测 模型

2024

现代工业经济和信息化

现代工业经济和信息化

影响因子:0.485
ISSN:
年,卷(期):2024.14(10)