Page 329 - 《环境工程技术学报》2023年第1期
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Vol.13,No.1 环 境 工 程 技 术 学 报 第 13 卷,第 1 期
Jan.,2023 Journal of Environmental Engineering Technology 2023 年 1 月
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能昌信,张弦,刘景财,等. 受 HDP 膜影响下的垃圾填埋场渗滤液水位探测方法研 究 [J].环境工程技术学报,2023,13(1):325-331.
NAI C X,ZHANG X,LIU J C,et al.Study on detection method of landfill le achate level affected by HDPE membrane[J].Journal of Environmental
Engineering Technology,2023,13(1):325-331.
受 HDP 膜影响下的垃圾填埋场渗滤液水位
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探测方法研究
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能昌信 ,张弦 ,刘景财 ,徐亚 2
1.山东工商学院信息与电子工程学院
2.中国环境科学研究院固体废物污染控制技术研究所
摘要 渗滤液水位会影响填埋场堆体稳定并有渗漏污染风险,当渗滤液赋存 于 HDP 防渗膜上方,堆体和渗滤液堆积电阻率特
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征的极端分异特性以及边界效应等因素使得最小二乘(LS)等传统物探反演方法无法精确反演实际电阻率分布,从而无法根据
电阻率差异特征定 位 HDP 膜上方渗滤液水位的高度。为准确刻画堆体内部特别是渗滤液-HDP 膜局部电阻率精细分布,对
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传统高密度电 法 (ERT 装置进行改进,提出了一种川形探测装 置 (C-ERT),并采 用 B 神经网络的电阻率反演模型算法。通过
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COMSO 理论模型和江西某生活垃圾填埋场采集的现场数据对该方法进行验证,并 与 L 法比较。结果表明:基于川形装置的
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B 神经网络能有效识别 出 HDP 膜上方的渗滤液区域,识别准确率约 为 83.2%, 而 L 法并不能识别出渗滤液区域。
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关键词 渗滤液水位;高密度电法;HDP 膜;B 神经网络;最小二乘算法;COMSO 模型
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中图分类号:705 文章编号:1674-991X(2023)01-0325-07 doi:10.12153/j.issn.1674-991X.20210864
Study on detection method of landfill le achate level affected by HDPE membrane
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NAI Changxin , ZHANG Xian , LIU Jingcai , XU Ya 2
1.School of Information and Electronic Engineering, Shandong Technology and Business University
2.Research Institute of Solid Waste Management, Chinese Research Academy of Environmental Sciences
Abstract The water level of leachate will affect the stability of landfill and have the risk of leakage and pollution.
When the leachate is stored on the HDPE impermeable membrane, the extreme differentiation characteristics of the
resistivity characteristics of the two and the boundary effect and other factors make the least squares and other
traditional geophysical inversion methods unable to accurately invert the actual resistivity distribution, and then
according to the resistivity the difference feature locates the height of the leachate water level above the HDPE
membrane. In order to accurately describe the fine distribution of the local resistivity of the leachate-HDPE
membrane inside the garbage dump, The traditional high density electrical method (ERT) device is improved, and a
detection device (C-ERT) is proposed, and the resistivity inversion model algorithm of BP neural network is
adopted. The method is verified by COMSOL theoretical model and field data collected from a domestic waste
landfill in Jiangxi Province, and compared with the least square algorithm (LS). The results show that the BP
algorithm based on C-ERT can effectively identify the leachate area above HDPE membrane, and the recognition
accuracy is about 83.2%, while LS inversion algorithm can not identify the leachate area.
Key words leachate level; electrical resistivity tomography; HDPE membrane; BP neural network; least squares
algorithm; COMSOL model
目前我国城市固体废物的处理方式仍以填埋为 水位过高会对堆体稳定性造成很大影响。我国多数
主,填埋场的堆体高度随着城市垃圾清运量的增长 填埋场运行数年后,渗滤液导排系统会出现淤堵失
而不断增加,堆体稳定性问题也随之暴露。填埋场 效等问题,在一些南方地区由于天气湿润多雨,加上
一旦出现失稳破坏,会引起渗滤液外流、废气排放等 填埋场雨污分流系统不完善,导致这些地区填埋场
环境污染问题,甚至还会造成人员伤亡 [1-2] 。渗滤液 渗滤液水位普遍较高,容易发生堆体失稳事故 。而
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收稿日期:2021-12-25
基金项目:国家重点研发计划项 目 (2020YFC1806304,2018YFC1800902);国家自然科学基金项 目 (51708529)
作者简介:能昌 信 (1965—),男,教授,博士,主要研究方向为环境监测技术,naicx@126.com