Research on Internal Parameter Filtering of Natural Gas Pipeline under Duty Cycle Transmission Mechanism

Authors

  • Xuqing Lu

DOI:

https://doi.org/10.54691/fse.v2i6.968

Keywords:

Natural Gas Pipeline Flow System, Duty Cycle Transmission Mechanism, Recursive Filtering, Collaborative Filtering

Abstract

In recent years, with the continuous growth of China's long-distance oil and gas pipeline network, wireless communication network applications have become more and more extensive with the continuous promotion of intelligent oilfield construction, while the energy-saving problem in the process of information transmission has become increasingly prominent. In order to ensure the sustainable development of China's oil and gas industry, low-power wireless transmission has become a basic requirement for the current intelligent oil and gas pipeline communication construction. For the monitoring of pipeline operating conditions, pressure and flow rate values are important parameters. If the accuracy and comprehensiveness of pipeline operation data can be ensured simultaneously under an energy-efficient transmission mechanism, it will provide strong support for the green and safe operation of pipelines. Therefore, in this paper, a recursive filtering study is conducted for natural gas gathering pipeline flow system under duty cycle transmission mechanism to complete the reliable monitoring of pipeline fluid transportation status.

Downloads

Download data is not yet available.

References

Gao H, Han F, Jiang B, et al. Recursive filtering for time-varying systems under duty cycle scheduling based on collaborative prediction[J]. Journal of the Franklin Institute, 2020, 357(17): 13189-13204. DOI: https://doi.org/10.1016/j.jfranklin.2020.09.035

Xu Jianjun, Huang Lida, Yan Limei, Yi Na. Insulator Self-Explosion Defect Detection Based on Hierarchical Multi-Task Deep Learning[J]. Transactions of China Electrotechnical Society, 2021,36(07):1407-1415.

Limei,LIU Yongqiang,XU Jianjun,et al.Broken string diagnosis of composite insulator based on Grabcut segmentation and filler area discrimination[J].Power System Protection and Control,2021,49(22):114-119.

Yi, Q. Wang, L. Yan, et al., A multi-stage game model for the false data injection attack from attacker’s perspective. Sustainable Energy Grids & Networks 28 (2021). DOI: https://doi.org/10.1016/j.segan.2021.100541

Na Yi,Jianjun Xu,Limei Yan,Lin Huang. Task Optimization and Scheduling of Distributed Cyber-physical System Based on Improved Ant Colony Algorithm. Future Generation Computer Systems, 109(Aug. 2020),134-148. DOI: https://doi.org/10.1016/j.future.2020.03.051

Yang Zhao, Jianjun Xu, Jingchun Wu. A New Method for Bad Data Identification of Oilfield Power System Based on Enhanced Gravitational Search-Fuzzy C-Means Algorithm. IEEE Transactions on Industrial Informatics. VOL. 15, NO. 11, NOVEMBER 2019 5963-5970. DOI: https://doi.org/10.1109/TII.2019.2935749

Jing Han,Xi Wang,LiMei Yan, Aida Dahlak, et al. Modelling the performance of an SOEC by optimization of neural network with MPSO algorithm. International Journal of Hydrogen Energy, Volume 44, Issue 51, 22 October 2019, Pages 27947-27957.Bae E Y, Yu S J. Transitive similarity evaluation model for improving sparsity in collaborative filtering[J]. Journal of KIIT, 2018, 16(12): 109-114. DOI: https://doi.org/10.1016/j.ijhydene.2019.09.055

Kluver D, Ekstrand M D, Konstan J A. Rating-based collaborative filtering: algorithms and evaluation[J]. Social Information Access, 2018: 344-390. DOI: https://doi.org/10.1007/978-3-319-90092-6_10

Shi Y, Larson M, Hanjalic A. Collaborative filtering beyond the user-item matrix: A survey of the state of the art and future challenges[J]. ACM Computing Surveys (CSUR), 2014, 47(1): 1-45. DOI: https://doi.org/10.1145/2556270

Downloads

Published

2022-06-22

Issue

Section

Articles