Li Xiaoke, Zhang Xiaofei, Dong Shengwen, Li Ansheng, Wang Liqing, Ming Wuyi
Henan Key Lab of Intelligent Manufacturing of Mechanical Equipment, Zhengzhou University of Light Industry, Zhengzhou 450002, China.
Key Laboratory of Termite Control of Ministry of Water Resources, Hubei Water Resources Research Institute, Wuhan 430070, China.
Sensors (Basel). 2025 Jul 15;25(14):4404. doi: 10.3390/s25144404.
Termites pose significant threats to the structural integrity of embankments due to their nesting and tunneling behavior, which leads to internal voids, water leakage, or even dam failure. This review systematically classifies and evaluates current termite detection techniques in the context of embankment maintenance, focusing on physical sensing technologies and biological characteristic-based methods. Physical sensing methods enable non-invasive localization of subsurface anomalies, including ground-penetrating radar, acoustic detection, and electrical resistivity imaging. Biological characteristic-based methods, such as electronic noses, sniffer dogs, visual inspection, intelligent monitoring, and UAV-based image analysis, are capable of detecting volatile compounds and surface activity signs associated with termites. The review summarizes key principles, application scenarios, advantages, and limitations of each technique. It also highlights integrated multi-sensor frameworks and artificial intelligence algorithms as emerging solutions to enhance detection accuracy, adaptability, and automation. The findings suggest that future termite detection in embankments will rely on interdisciplinary integration and intelligent monitoring systems to support early warning, rapid response, and long-term structural resilience. This work provides a scientific foundation and practical reference for advancing termite management and embankment safety strategies.
白蚁因其筑巢和挖掘行为对堤坝的结构完整性构成重大威胁,这会导致内部空洞、漏水甚至堤坝坍塌。本综述在堤坝维护的背景下,系统地对当前白蚁检测技术进行了分类和评估,重点关注物理传感技术和基于生物特征的方法。物理传感方法能够对地下异常进行非侵入式定位,包括探地雷达、声学检测和电阻成像。基于生物特征的方法,如电子鼻、嗅探犬、目视检查、智能监测和基于无人机的图像分析,能够检测与白蚁相关的挥发性化合物和表面活动迹象。该综述总结了每种技术的关键原理、应用场景、优点和局限性。它还强调了集成多传感器框架和人工智能算法作为提高检测准确性、适应性和自动化的新兴解决方案。研究结果表明,未来堤坝白蚁检测将依赖跨学科整合和智能监测系统,以支持早期预警、快速响应和长期结构恢复力。这项工作为推进白蚁管理和堤坝安全策略提供了科学依据和实践参考。