极点特征聚类的公路隐藏裂缝自动识别算法Automatic Recognition Algorithm for Hidden Cracks in Highway Based on Pole Feature Clustering
周丽军
摘要(Abstract)：
对公路隐藏裂缝病害的无损检测与识别在公路养护中尤为重要,然而通常利用地质雷达检测获得的B-scan图像多是依靠其双曲线特征获得目标的位置信息,对目标介电属性等方面的深入研究还存在困难。对此该文提出一种基于极点特征聚类的地质雷达公路隐藏裂缝自动识别算法。首先对回波信号进行奇异值分解,提取体现目标信号的大奇异值,重构回波信号,由此不仅对回波信号进行降维,还去除了噪声干扰。通过解卷积过程获得目标的冲激响应,利用奇点展开法提取其晚时响应部分的极点信息,构建极点特征空间,根据已知环境样本对极点进行初始聚类中心优化并取其均值,利用此均值初始聚类中心对待识别目标回波的极点特征空间进行聚类。实验结果验证了算法的有效性。
关键词(KeyWords)： 极点特征;探地雷达;公路裂缝;奇异值分解
基金项目(Foundation): 国家自然科学基金(51705299);; 山西省青年科技研究基金(201801D221047)
作者(Author): 周丽军
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