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Research on Intelligent Location Method of Water Supply Pipe Network Burst Based on BP Neural Network Deep Learning

机译：基于BP神经网络深度学习的供水管网爆裂智能定位方法研究。

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Based on the in-depth analysis of the causes of the large-scale water supply pipe network explosion at home and abroad, the paper discusses the neural network modeling technology for quickly and accurately locating the water pipe network. Furthermore, the remedial measures of the pipe network squib in the field were adopted, and the BP neural network deep learning method was proposed to carry out the intelligent positioning of the water pipe network bursting. Based on the construction of a miniature hydraulic model based on BP neural network analysis, through the correlation analysis of the flow change of 5 positions and the pressure monitoring point change of 17 positions when the pipe network bursts, the artificial neural network deep learning is further used to diagnose the position of the pipe network where the pipe burst is located. In this paper, the small-scale water supply pipe network built by the laboratory is taken as an example to verify the research method of the pipe burst positioning.
机译：在深入分析国内外大型供水管网爆炸的原因的基础上，探讨了用于快速准确定位供水管网的神经网络建模技术。此外，采用了现场管网爆管的补救措施，并提出了BP神经网络深度学习方法来进行水管网爆破的智能定位。在基于BP神经网络分析的微型水力模型构建的基础上，通过对管网爆裂时5个位置的流量变化和17个位置的压力监测点变化的相关性分析，进一步进行了人工神经网络深度学习用于诊断管道破裂所在的管网位置。本文以实验室建立的小型供水管网为例，验证了爆管定位的研究方法。

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