论文标题
智能特征提取，数据融合和混凝土桥裂纹的检测：当前的发展和挑战
Intelligent Feature Extraction, Data Fusion and Detection of Concrete Bridge Cracks: Current Development and Challenges
论文作者
论文摘要
作为混凝土桥的常见外观缺陷，裂缝是桥梁结构健康评估的重要指标。尽管对裂纹识别进行了很多研究，但对桥梁裂缝的演化机制的研究仍然远非实际应用。在本文中，全面审查了基于数据驱动方法的智能特征提取，数据融合和裂纹检测的智能理论和方法的最新研究。从三个方面进行了讨论：桥梁裂纹的多模式参数的特征提取水平，描述水平和桥梁裂纹损伤状态的诊断水平。我们专注于以前的研究，涉及桥梁裂纹的多模式参数的定量表征问题及其在裂纹识别中的实现，同时突出了它们的一些主要缺点。此外，讨论了当前的挑战和潜在的未来研究方向。
As a common appearance defect of concrete bridges, cracks are important indices for bridge structure health assessment. Although there has been much research on crack identification, research on the evolution mechanism of bridge cracks is still far from practical applications. In this paper, the state-of-the-art research on intelligent theories and methodologies for intelligent feature extraction, data fusion and crack detection based on data-driven approaches is comprehensively reviewed. The research is discussed from three aspects: the feature extraction level of the multimodal parameters of bridge cracks, the description level and the diagnosis level of the bridge crack damage states. We focus on previous research concerning the quantitative characterization problems of multimodal parameters of bridge cracks and their implementation in crack identification, while highlighting some of their major drawbacks. In addition, the current challenges and potential future research directions are discussed.
