基于ResNet-UNet模型的DAS矸石浆体充填堵管监测技术

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中图分类号：TD528.1 文献标志码：A 文章编号：1672-9315（2025）04-0650-13

DOI：10. 13800/j. cnki. xakjdxxb.2025.0402

DAS gangue slurry filling pipe blockage monitoring technology based on ResNet-UNet model

CHAI Jing1，²， WANG Ziming'，MA Chenyang'， ZHANG Dingding1，2，LI Zhi 1 ZHOU Sen'，QIU Fengqi，3， WU Yuyi³，JI Wenli1²，ZHAO Pengxiang4 （1. College of Energyand Mining Engineering，Xi’an Universityof Science and Technology， Xi'an 710o54，China; 2. Key Laboratory of Western Mine Exploitation and Hazard Prevention，Ministry of Education， Xi'an University of Science and Technology，Xi'an 710o54， China; 3.China Coal Energy Research Institute Co.， Ltd.，Xi’an 710o54，China;

4. College of Safety Science and Engineering， Xi'an University of Science and Technology，Xi'an 71Oo54， China）

Abstract： The coal gangue slurry transportation pipeline is prone to issues such as blockage and corrosion during the transportation process.At present， precise positioning still faces huge challenges in addressing the blockage problem in slurry pipeline transportation. A method combining image noise reduction with a ResNet-UNet composite network was proposed for monitoring and identifying blockage points ，using Distributed Acoustic Sensing as the monitoring technique; In order to evaluate the proposed solution，a 15.14 meter ring pipe model was constructed，and a grouting blockage simulation test was conducted.The results demonstrate that： Compared with traditional UNet and ResNet models，the ResNet-UNet network can accurately identify blockage point images while effectively mitigating the issue of gradient explosion， the blockage location accuracy reaches 97. 83% ，with a precision of 97.76% ，a recall rate of 94.80% ，and an F1 score of O.958 9.This study successfully addresses the noise processing challenges associated with the high sensitivity of DAS-based monitoring， significantly improving the accuracy of blockage point positioning within the scope of comprehensive coal gangue pipeline monitoring，it provides an intelligent and precise solution for monitoring coal gangue slurry transportation pipelines and identifying blockage points.

Key words： Distributed Acoustic Sensing; gangue slurry pipeline transportation; noise reduction algorithms; ResNet-UNet model; image recognition; blockage localization

0 引言

在煤炭等矿产资源开采过程中，大量矸石废弃物的高效运输和管理是实现绿色开采的重要环节[1-3]。（剩余17635字）