基于机器先验与WTC-GAN的桥梁吊杆视频去遮挡方法A Machine-Prior-Guided WTC-GAN Framework for Occlusion Removal and Restoration in Bridge Hanger Videos
亓兴军,公杰,张玉宝,施建州,王哲,陈允泉
摘要(Abstract):
为了提升受遮挡吊杆的频率识别精度,提出一种基于机器先验引导与弱时序约束的视频修复方法。采用孤立森林算法无监督检测并标注视频遮挡区域,生成二进制掩模作为机器先验;构建弱时序约束生成对抗网络(weak temporal constraint generative adversarial network, WTC-GAN),以遮挡帧及其时序上下文为输入,引入光流一致性损失作为约束条件,以约束微振动轨迹的时序连续性及遮挡区域重建结果的运动一致性。研究结果表明:该方法的视觉修复质量显著优于传统方法,峰值信噪比(peak signal-to-noise ratio, PSNR)与结构相似性(structural similarity, SSIM)分别提升2.96 dB和5.85%;修复后视频的频率分析结果与无遮挡状态高度一致,平均相对误差仅为1.14%。该方法在不同程度的遮挡工况下表现出良好的鲁棒性,客观界定了极端长时遮挡的性能边界,且对斜拉索等同类线状构件具备普适性,展现出在桥梁视觉监测中的重要工程应用潜力。
关键词(KeyWords): 桥梁健康监测;视频修复;生成对抗网络;吊杆频率;遮挡处理
基金项目(Foundation): 济青高速铁路有限公司科技计划项目(JQKJ2024-10);; 山东省住房城乡建设科技计划项目(2024KYKF-CSGX024);山东省住房城乡建设科技计划项目(2023-017)
作者(Author): 亓兴军,公杰,张玉宝,施建州,王哲,陈允泉
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