Research Status of Danger Detection and IdentificationTechnology of Dike Engineering

HAO Yan-jie, ZHANG Jian-qiang, GUO Cheng-chao

Journal of Changjiang River Scientific Research Institute ›› 2019, Vol. 36 ›› Issue (10) : 73-78.

PDF(1094 KB)
PDF(1094 KB)
Journal of Changjiang River Scientific Research Institute ›› 2019, Vol. 36 ›› Issue (10) : 73-78. DOI: 10.11988/ckyyb.20190874
SAFE OPERATION ,MONITORING AND EARLY WARNING OF DYKE ENGINEERING

Research Status of Danger Detection and IdentificationTechnology of Dike Engineering

  • HAO Yan-jie1, ZHANG Jian-qiang2, GUO Cheng-chao1
Author information +
History +

Abstract

The research status of detection and identification technologies for hidden dangers or disasters of dike project, including piping and dam break, are summarized. The characteristics, applicability, and engineering application of common methods in detecting hidden dangers of dike, namely, high-density resistivity method, ground penetration radar imaging, magnetoelectric method, transient electromagnetic method, and flow field method, are analyzed. Moreover, the theories and engineering practices of hidden danger identification technologies based on experts’ experiences, event tree analysis, sensitivity analysis, neural network, grey theory and artificial intelligence are expounded. The related theories provide necessary theoretical foundations for some existing problems and engineering applications that will be carried out in the future.

Key words

dike engineering / hidden danger detection / danger identification / piping / dam break

Cite this article

Download Citations
HAO Yan-jie, ZHANG Jian-qiang, GUO Cheng-chao. Research Status of Danger Detection and IdentificationTechnology of Dike Engineering[J]. Journal of Changjiang River Scientific Research Institute. 2019, 36(10): 73-78 https://doi.org/10.11988/ckyyb.20190874

References

[1] 董浩斌,王传雷.高密度电法的发展与应用[J].地学前缘,2003(1):171-176.
[2] 刘昌军,赵进勇,孙东亚, 等.高密度电法仪在工程隐患探测中的应用[J].水利水电技术,2007(2):90-94.
[3] 颜 钟. 基于BP人工神经网络的高密度电法反演理论应用研究[D].武汉:raybet体育在线 ,2012.
[4] 吴 晋,徐兴新,吴相安, 等.各类水利工程隐患的探地雷达影像识别与分析[J].水利水电技术,1998(8):25-30.
[5] ALLROGGEN N, BOOTH A D, BAKER S E, et al. High-resolution Imaging and Monitoring of Animal Tunnels Using 3D Ground-penetrating Radar[J]. Near Surface Geophysics, 2019,17(3): 291-198.
[6] HUBER E, ANDERS B, HUGGENBERGER P. Imaging Scours in Straightened and Braided Gravel-bed Rivers with Ground-penetrating Radar[J]. Near Surface Geophysics, 2019, 17(3): 263-276.
[7] 岳全贵,张 杨,肖国强, 等. 探地雷达的常见干扰和不良地质体的超前预报在隧道工程中的应用[J].raybet体育在线 院报,2017,34(8):36-40.
[8] 邓靖武. 磁电法正演理论研究[D].北京:中国地质大学(北京),2005.
[9] 翁爱华,李斯睿,杨 悦,等.磁电法基本原理、发展现状及前景展望[J].吉林大学学报(地球科学版),2017,47(6):1838-1854.
[10] TADA N, SEAMA N, GOTO T-N, et al. 1-D Resistivity Structures of the Oceanic Crust around the Hydrothermal Circulation System in the Central Mariana Trough Using Magnetometric Resistivity Method[J]. Earth, Planets and Space, 2005, 57(7): 673-677.
[11]JING Rong-zhong, ZENG You-qiang, HUANG Li-shan. Application in Deep Mining of Gold Mine Water Damage with a Magnetic Source Transient Electromagnetic Method[J]. Acta Geologica Sinica, 2019, 93:292-293.
[12]邹声杰. 堤坝管涌渗漏流场拟合法理论及应用研究[D].长沙:中南大学,2009.
[13]何继善.广域电磁法和拟流场法精细探测技术:以井工一矿水害探测为例[J].Engineering,2018,4(5):188-205.
[14]丁留谦,张启义,姚秋玲.1998年长江流域管涌险情特点分析[J].水利水电技术,2007(2):44-45,69.
[15]孙佰清,潘启树,冯英浚,等.提高BP网络训练速度的研究[J].哈尔滨工业大学学报,2001,33(4):439-441.
[16]许廷发,张 敏,顾海军, 等. 改进的BP算法在多目标识别中的应用[J].光学精密工程, 2003(5):513-515.
[17]MARCHE C,ROBERT B.Dam Failure Risk:Its Definition and Impact on Safety Assessment of Dam Structures[J].Journal of Decision Systems,2002,11(3/4):513-534.
[18]梁国坚,杜鑫峰,陶熠昆, 等.基于图像处理技术的险情识别智能巡检机器人的研究[J].自动化与仪器仪表,2017(6):10-12.
[19]陆 峰. 边坡监测的模式识别和极限分析研究[D].北京:中国水利水电科学研究院,2001.
[20]YANG B. Dynamic Risk Identification Safety Model Based on Fuzzy Support Vector Machine and Immune Optimization Algorithm[J]. Safety Science, 2019, 118: 205-211.
[21]CATTLEMAN K R.数字图像处理[M]. 朱志刚,林学阎,石定机, 等,译.北京:电子工业出版社,2004:378-406.
[22]BOWLES D S. Evaluation and Use of Risk Estimates in Dam Safety Decision-making[C]//Proceedings of the United Engineering Foundation Conference on Risk-based Decision-making in Water Resources IX:20-Year Retrospective and Prospective of Risk-based Decision-making. American Society of Civil Engineers. Santa Barbara, California. August, 2001: 17e32.
[23]REN P F, WU A Y, SHI S L. Analyzing the Risk of Road Tunnel Fire Based on Fuzzy Fault Tree Method[J]. Journal of Hunan University of Science and Technology (Natural Science Edition), 2013, 28: 17-21.
[24]吴中如,金永强,马福恒, 等.水库大坝的险情识别[J].中国水利,2008(20):32-33,28.
[25]骆辛磊.堤防险情严重程度划分与识别方法探讨[J].水利水电科技进展,2003,23(2):21-24.
[26]SADEGHI A, FARHAD H, MOGHADDAM A M, et al. Identification of Accident-prone Sections in Roadways with Incomplete and Uncertain Inspection-based Information: A Distributed Hazard Index Based on Evidential Reasoning Approach[J]. Reliability Engineering and System Safety, doi: 10.1016/j.ress.2018.06.020.
[27]ROMER C, FERENTINOU M. Shallow Landslide Susceptibility Assessment in a Semiarid Environment-A Quaternary Catchment of KwaZulu-Natal, South Africa[J]. Engineering Geology, doi: 10.1016/j.enggeo.2015.12.013.
PDF(1094 KB)

Accesses

Citation

Detail

Sections
Recommended

/

Baidu
map