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作 者:廖乾国 李钧 李兴财[2,3] LIAO Qianguo;LI Jun;LI Xingcai(School of Electronic and Electrical Engineering,Ningxia University,Yinchuan 750021,China;Ningxia Key Laboratory of Desert Information&Intelligent Sensing,Ningxia University,Yinchuan 750021,China;School of Physics,Ningxia University,Yinchuan 750021,China;School of Information Engineering,Tarim University,Alaer 843300,China)
机构地区:[1]宁夏大学电子与电气工程学院,宁夏银川750021 [2]宁夏大学宁夏沙漠信息智能感知重点实验室,宁夏银川750021 [3]宁夏大学物理学院,宁夏银川750021 [4]塔里木大学信息工程学院,新疆阿拉尔843300
出 处:《宁夏工程技术》2024年第2期180-184,192,共6页Ningxia Engineering Technology
基 金:兰州大学中央高校基本科研业务费专项资金资助项目(lzujbky-2022-kb08);宁夏回族自治区创新领军人才培养计划项目(2020GKLRLX08);宁夏自然科学基金项目(2022AAC03643)。
摘 要:针对积沙检测实时性差、易受天气因素影响、积沙量化指标不明确等问题,提出了一种基于图像处理的铁轨积沙检测方法,使用单尺度Retinex算法处理了沙尘天气条件下的铁轨积沙图像,通过铁轨未积沙区域特征提取和最大类间方差法对含有阴影的铁轨积沙图像进行了阈值分割,综合两次图像分割结果并获取了积沙信息。此外,基于铁路沙害等级划分指标对提取的积沙信息进行了沙害等级划分,最终实现了不同天气条件下的铁轨积沙检测。结果表明,该方法能够在晴天和沙尘天气下准确获得铁轨积沙状况并根据对应沙害等级提供预警。To address the issues of poor real-time performance,susceptibility to weather factors,and unclear quantification indicators of sand accumulation detection on railway tracks,a railway sand accumulation detection method based on image processing is proposed.The single-scale Retinex algorithm is utilized to process images of railway tracks sand accumulation under sand and dust weather conditions.The threshold segmentation of the images containing shadows is performed through feature extraction of non-sand accumulation areas and the maximum inter-class variance method,and sand accumulation information is obtained by integrating the results of two image segmentation.Additionally,based on the division index of railway sand hazard levels,the extracted sand accumulation information is graded according to the corresponding sand hazard levels,achieving sand accumulation detection on railway tracks under different weather conditions.Experimental results demonstrate that this method can accurately obtain the status of sand accumulation on railway tracks under both sunny and dusty weather conditions and provide warnings according to corresponding sand hazard levels.
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