非金属管道电阻率成像效果数值模拟研究
Numerical Simulation Study on the Imaging Effect of Non-Metallic Pipeline Resistivity
摘要: 非金属管道被广泛用于城市地下管线中，是城市基础设施的重要组成部分，但非金属管道具有非导电导磁和绝缘性，在管线探测中是一个难题。本文采用数值模拟方法，对不同间距、不同直径、不同埋深的非金属管道的电阻率成像特点进行数值模拟研究。结果表明：当两根非金属管道横向排列间距较大时，电阻率成像能够清晰分辨两管道位置，但随着管道间距变小，电阻率成像难以对两根管道进行区分。两根较粗管道，对应两管道位置出现高阻异常区，两高阻异常区相连通，在两管道中间下方出现下凸的高阻异常，对应两管道的中间位置。当两管道纵向排列时，上下两根管道形成一个异常区，电阻率成像难以在垂向上区分两根管道。
Abstract: Non metallic pipelines are widely used in urban underground pipelines and are an important component of urban infrastructure. However, non-metallic pipelines have non-conductive, magnetic, and insulating properties, making them a challenge in pipeline detection. This paper uses numerical simulation methods to study the electrical resistivity imaging characteristics of non-metallic pipelines with different spacing, diameter, and burial depth. The results indicate that when the horizontal spacing between two non-metallic pipelines is large, resistivity imaging can clearly distinguish the positions of the two pipelines, but as the spacing between pipelines decreases, resistivity imaging is difficult to distinguish between the two pipelines. Two thicker pipelines have high resistance abnormal areas corresponding to the positions of the two pipelines. The two high resistance abnormal areas are connected, and a convex high resistance abnormal area appears below the middle of the two pipelines, corresponding to the middle position of the two pipelines. When two pipelines are arranged vertically, the upper and lower pipelines form an abnormal area, making it difficult for resistivity imaging to distinguish the two pipelines vertically.
文章引用：穆路谦, 曹志鹏, 黄思俊, 陈宝佳, 王明明. 非金属管道电阻率成像效果数值模拟研究[J]. 自然科学, 2023, 11(5): 753-759. https://doi.org/10.12677/OJNS.2023.115090

参考文献

[1] 陈思静, 胡祥云, 彭荣华. 城市地下管线探测研究进展与发展趋势[J]. 地球物理学进展, 2021, 36(3): 1236-1247.
[2] Xu, Y., Li, J., Zhang, M., et al. (2020) Pipeline Leak Detection Using Raman Distributed Fiber Sensor with Dynamic Threshold Identification Method. IEEE Sensors Journal, 20, 7870-7877. [Google Scholar] [CrossRef] 
[3] Ge, L., Zhang, C., Tian, G., et al. (2021) Current Trends and Perspectives of Detection and Location for Buried Non-Metallic Pipelines. Chinese Journal of Mechanical Engi-neering, 34, Article No. 97. [Google Scholar] [CrossRef] 
[4] 邱小峰. 高密度电阻率法在探测地下雨污水管道中的应用[J]. 工程地球物理学报, 2019, 16(1): 97-100.
[5] Baroudi, U., Al-Roubaiey, A. and Devendiran, A. (2019) Pipeline Leak Detection Systems and Data Fusion: A Survey. IEEE Access, 7, 97426-97439. [Google Scholar] [CrossRef] 
[6] Liu, J., Zang, D., Liu, C., Ma, Y. and Fu, M. (2019) A Leak Detection Method for Oil Pipeline Based on Markov Feature and Two-Stage Decision Scheme. Measurement, 138, 433-445. [Google Scholar] [CrossRef] 
[7] Zhang, H., Hu, X., Ma, D., Wang, R. and Xie, X. (2020) Insufficient Data Generative Model for Pipeline Network Leak Detection Using Generative Adversarial Networks. IEEE Transactions on Cybernetics, 52, 7107-7120. [Google Scholar] [CrossRef] 
[8] 韩沙沙, 王照天, 郭凯. 地下管线探测方法综述[J]. 测绘通报, 2016(S1): 104-106+109.
[9] Razvarz, S., Jafari, R. and Gegov, A. (2021) A Review on Different Pipeline Defect Detection Techniques. In: Flow Modelling and Control in Pipeline Systems. Studies in Systems, Decision and Control, Vol. 321, Springer, Cham, 25-57. [Google Scholar] [CrossRef] 
[10] 丁华, 朱谷兰, 汪大鹏. 深埋管线探测方法技术分析探讨[J]. 工程地球物理学报, 2010, 7(3): 390-393.
[11] 区福帮. 城市地下管线普查技术研究与应用[M]. 南京: 东南大学出版社, 1998: 104-123.
[12] Li, J., Zheng, Q., Qian, Z. and Yang, X. (2019) A Novel Location Algorithm for Pipeline Leakage Based on the Attenuation of Negative Pressure Wave. Process Safety and Environmental Protection, 123, 309-316. [Google Scholar] [CrossRef] 
[13] Guan, M., Cheng, Y., Li, Q., et al. (2019) An Effective Method for Submarine Buried Pipeline Detection via Multi-Sensor Data Fusion. IEEE Access, 7, 125300-125309. [Google Scholar] [CrossRef] 
[14] Wang, S., Ananthanarayanan, G., Zeng, Y. and Goel, N. (2019) High-Throughput CNN Inference on Embedded ARM Big. LITTLE Multicore Processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 39, 2254-2267. [Google Scholar] [CrossRef] 
[15] 张玮, 肖宏跃, 钟宙灿. 高密度电阻率法在城市地下水网管道探测中的应用[J]. 工程勘察, 2009, 37(7): 91-94.
[16] 程甄, 欧元超. 基于高密度电法的地下给水管道泄露点检测研究[J]. 安徽理工大学学报(自然科学版), 2019, 39(6): 73-76.
[17] 黄俊革, 沈云发, 阮百尧, 鲍光淑. 坑道内金属管道对电阻率测深影响[J]. 石油地球物理勘探, 2004(S1): 52-56.
[18] 王磊. 密度电法在水文孔管道验证中的应用[J]. 西部资源, 2019(1): 150-151.