测试技术学报2024，Vol.38Issue(3)：315-322,8.DOI:10.3969/j.issn.1671-7449.2024030
基于特征增强的汽车发动机积碳程度识别模型
Recognition Model of Automobile Engine Carbon Deposits Degree Based on Feature Enhancement
摘要
Abstract
Long-term accumulation of carbon deposits in automobile engines can easily accelerate the age-ing of automobiles.Timely detection and cleaning can effectively prolong the service life of automobiles.In this paper,a carbon deposits degree recognition method based on a visual image is proposed to auto-matically recognitze the degree of carbon deposits and provide guidance for carbon deposits cleanup.Firstly,to address the issue of small data volume and uneven category distribution in carbon deposits images dataset,data preprocessing is conducted.Secondly,aimed at the wide range of feature distribution and fine-grained characteristics of carbon images,a feature resampling module is designed to improve the feature expression from both spatial and channel directions.Finally,a lightweight carbon deposits degree recognition model is designed to facilitate the detection of deployed.The experimental results demonstrate that compared to other methods,the method proposed in this thesis achieves the highest inference speed of 179 frames/s with a testing accuracy of 84.5%,meeting the needs of the industry.关键词
积碳程度识别/小样本学习/细粒度图像/特征重采样/轻量化模型Key words
recognition of the degree of carbon deposits/few-shot learning/fine-grained images/feature resampling/lightweight model分类
信息技术与安全科学引用本文复制引用
张永玲,黄倩,陈友兴,陈香,张航佳..基于特征增强的汽车发动机积碳程度识别模型[J].测试技术学报,2024,38(3):315-322,8.基金项目
山西省回国留学人员科研资助项目(2022-145) （2022-145）
