管道泄漏诊断技术在保障管道系统安全运行中起着至关重要的作用。首先，介绍了管道泄漏诊断系统的结构，并指出由单一管段向复杂管网泄漏诊断的发展趋势。进一步从基于数据驱动的传统泄漏检测方法、管道泄漏信号源定位技术和基于深度学习的复杂管网泄漏检测方法 3 个方面进行综述，分析了不同方法的优势、局限性和适用范围。最后指出，随着管网系统的复杂度增加，传统方法的局限性逐渐显现，基于深度学习技术的复杂管网微弱泄漏诊断、多源信号融合和管网智能化的研究将成为未来的研究趋势。

Pipeline leak diagnosis technology plays a crucial role in ensuring the safe operation of pipeline systems. Firstly, the structure of pipeline leak diagnosis systems is introduced, and the trend of transitioning from single pipeline segments to complex pipeline networks for leak diagnosis is highlighted. Furthermore, a review is provided on traditional leak detection methods based on data-driven approaches, pipeline leak source localization techniques, and complex pipeline network leak detection methods based on deep learning. The advantages, limitations, and applicability of different methods are analyzed. Finally, it is pointed out that with the increasing complexity of pipeline network systems, the limitations of traditional methods are gradually becoming apparent, and research on deep learning-based techniques for detecting minor leaks in complex pipeline networks, multi-source signal fusion, and pipeline network intelligence is identified as future research trends.