Open Access
| Issue |
E3S Web Conf.
Volume 257, 2021
5th International Workshop on Advances in Energy Science and Environment Engineering (AESEE 2021)
|
|
|---|---|---|
| Article Number | 03070 | |
| Number of page(s) | 6 | |
| Section | Environmental Monitoring Repair and Pollution Control | |
| DOI | https://doi.org/10.1051/e3sconf/202125703070 | |
| Published online | 12 May 2021 | |
- Guangmin Zhang, Ping Yang, Sihong He, Yu Zheng, Gangbing Song. A power waveform design based on OVSF-PPM for stress wave based wireless power transfer[J]. Mechanical Systems and Signal Processing, 2021, 147. [Google Scholar]
- Liang Ren, Tao Jiang, Zi-guang Jia, Dong-sheng Li, Chao-lin Yuan, Hong-nan Li. Pipeline corrosion and leakage monitoring based on the distributed optical fiber sensing technology[J]. Measurement, 2018, 122. [Google Scholar]
- Li Hongtao. Study on propagation law of wellbore pressure wave in complex fluid medium [D]. Study on propagation law of wellbore pressure wave in complex fluid medium [D]Southwest Petroleum University, 2015. [Google Scholar]
- Guoxi He, Yongtu Liang, Yansong Li, Mengyu Wu, Liying Sun, Cheng Xie, Feng Li. A method for simulating the entire leaking process and calculating the liquid leakage volume of a damaged pressurized pipeline[J]. Journal of Hazardous Materials, 2017, 332. [PubMed] [Google Scholar]
- Meng Lingya, Fu Juntao, Li Yuxing, Liu Cuiwei, Liu Guangxiao. Journal of China University of Petroleum (Edition of Natural Science), 2013, 37(02):124-129. [Google Scholar]
- Yang Fan, Garden, Juna. Simulation and analysis of gas pipeline leakage dynamic process based on TGNET[J]. Journal of Chongqing University of Science and Technology (Natural Science Edition), 2013, 15(S1):94-98. [Google Scholar]
- Numerical Simulation Study on Leakage Location of Long Pipeline with Bifurcation Structure [D]. Xi ’an University of Technology, 2020. [Google Scholar]
- Xu Hailiang, Hu Wengang, Yang Fangqiong. Journal of Central South University (Science and Technology), 2019, 50(02):304-310. [Google Scholar]
- Zhu Hongwei, Kang Qianqian, Li Xinhong, Chen Guoming. Research on Leakage Law of Subsea Long Gas Pipeline Considering Process Control[J]. Journal of Safety Science and Technology, 2018, 14(06):114-120. [Google Scholar]
- Fu Juntao, Li Yuxing, Li Yutong, Wang Wuchang, Liu Guangxiao, Fang Liping. Production and propagation characteristics of gas pipeline leakage acoustic wave[J]. Oil and Gas Storage and Transportation, 2012, 31(08): 604611+647. [Google Scholar]
- Yang Zixuan, Fan Shidong, Jiang Pan, Xiong Ting. Research on Attenuation Coefficients of Negative Pressure Wave and Leakage Detection of Ordinary Elbow[J]. Journal of Wuhan University of Technology (Traffic Science & Engineering), 2012, 36(05):997-1000+1004. [Google Scholar]
- Feng Wenxing, Wang Zhaoqin, Cheng Wuyi. Comparison and Analysis of Small Hole Leakage Model and Large Hole Leakage Model in High Pressure Gas Pipeline[J]. Safety and Environmental Engineering, 2009, 16(04):108110. [Google Scholar]
- Wang Qiang, Zheng Xiaoliang, Xue Sheng, Yuan Hongyong, Fu Ming. A cross location method for gas pipeline leakage with time difference of wave and reach[J]. Applied Acoustics, 2020, 39(03):472-480. [Google Scholar]
- Li Chuanxian, Lu Wenwen, Shi Yanan, Du Shicong, Zheng Wangyu, Li Pengyu. Pipeline Leakage Condition Identification Based on Improved CEEMDan-Entropy Method[J]. Journal of Petrochemical Universities, 2020, 33(01):88-96. [Google Scholar]
- Ji Shangshang. Research on Leakage Monitoring System of Water Supply Pipeline Network [D]. Research on Leakage Monitoring System of Water Supply Pipeline Network [D]ebei University of Engineering, 2018. [Google Scholar]
- An Xingxing. Research on Pipeline Leak Detection Based on Deep Learning [D]. Research on Pipeline Leak Detection Based on Deep Learning [D] Northeast Petroleum University, 2018. [Google Scholar]
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