Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 2


Published
on

November 27, 2023


Pages


DOI

Article

Log specification and intelligent analysis method based on oil and gas pipeline SCADA system

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Authors

Lingyi Sun Affiliation:
Pipe China Oil and Gas Control Center, Beijing, 100000, China.
, Yafeng Li Affiliation:
Pipe China Oil and Gas Control Center, Beijing, 100000, China.
, Jingyang Zhang Affiliation:
Beijing Kedong Electric Power Control System Co., Ltd., Beijing, 100089, China.
, Jingli Yang Affiliation:
Pipe China Oil and Gas Control Center, Beijing, 100000, China.
, Bingqiang Mao Affiliation:
Pipe China Oil and Gas Control Center, Beijing, 100000, China.
, Zhonghua Deng Affiliation:
Pipe China Oil and Gas Control Center, Beijing, 100000, China.
and Wei Wang Affiliation:
Beijing Kedong Electric Power Control System Co., Ltd., Beijing, 100089, China.


Abstract

As the control center of the natural gas long-distance pipeline network, the SCADA system shoulders the important tasks of data collection and monitoring of the whole long-distance pipeline, gas transmission management, production scheduling, operation and maintenance coordination in production, and plays a very important role in the whole oil and gas pipeline. In this paper, firstly, the SCADA system for localized long-distance pipelines is explained in detail, including its basic structure and special solutions to problems. Secondly, the AdaBoost algorithm, which combines the MapReduce parallel computing framework, is introduced to collect and process data from the operation logs of the SCADA system and normalize the logs. Finally, to test the interaction between the improved AdaBoost algorithm and the SCADA system, a system test was conducted. The results show that the average latency of scheduling the logs of the SCADA system by AdaBoost algorithm with MapReduce parallel computing framework is only 39.82ms, the average processing speed of the log normalization file data under the multi-threaded mode of the system reaches 86.51GB/s, and the effective accuracy of the fault diagnosis is as high as 90.36%. This shows that the oil and gas pipeline SCADA system interacting with data visualization technology can process operation logs more quickly and can carry out real-time intelligent supervision of the working status and operation parameters of the whole auxiliary system, promoting the intelligent development of the oil and gas pipeline SCADA system.


Keywords

AdaBoost algorithm, SCADA system, MapReduce, Intelligent analysis, Fault diagnosis, 00A73


Citation

Sun, L., Li, Y., Zhang, J., Yang, J., Mao, B., Deng, Z., & Wang, W. (2023). Log specification and intelligent analysis method based on oil and gas pipeline SCADA system. Applied Mathematics and Nonlinear Sciences, 8(2). https://doi.org/10.2478/amns.2023.2.01261

Published by: Engineering Journals

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