Scholarlink

<p>In the leakage detection of reservoir dam bodies, traditional geophysical methods can only achieve one-time detection. Meanwhile, due to the non-uniqueness of geophysicalin version, how to improve the fidelity of geophysical detection inversion profiles has become a key challenge in the industry. This study aims to construct a long-term real-time monitoring system using the time-lapse resistivity method, reveal the spatiotemporal evolution law of dam leakage, and provide technical support for accurate treatment. By integrating the Internet of Things (IoT), 5G technology, and AI technology, real-time data acquisition, real-time transmission, and automatic inversionare realized. Through dynamic imaging analysis of the electrical anomaly characteristics of the leakage area and comparison between corresponding rainfall events, the leakage range and resistivity changes, the reliability and efficiency of dam leakagedete ction are significantly improved. This achieves long-termdynamic monitoring of dam leakage and provides a new perspective for the safe operation and maintenance of reservoirs.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Mechanism and Application of Dynamic Monitoring for Seepage Processes in Earth-Rock Dams Using the Time-Lapse Electrical Resistivity Method

  • 期刊论文

  • 发表日期：

    2025年11月4日

查看全文
  • Zu-gen Cai,
  • Ming-sheng Yang,
  • Jian-jun Wang,
  • Yao-hui Xu

摘要

In the leakage detection of reservoir dam bodies, traditional geophysical methods can only achieve one-time detection. Meanwhile, due to the non-uniqueness of geophysicalin version, how to improve the fidelity of geophysical detection inversion profiles has become a key challenge in the industry. This study aims to construct a long-term real-time monitoring system using the time-lapse resistivity method, reveal the spatiotemporal evolution law of dam leakage, and provide technical support for accurate treatment. By integrating the Internet of Things (IoT), 5G technology, and AI technology, real-time data acquisition, real-time transmission, and automatic inversionare realized. Through dynamic imaging analysis of the electrical anomaly characteristics of the leakage area and comparison between corresponding rainfall events, the leakage range and resistivity changes, the reliability and efficiency of dam leakagedete ction are significantly improved. This achieves long-termdynamic monitoring of dam leakage and provides a new perspective for the safe operation and maintenance of reservoirs.