An Improved High-Intelligence Method of Gas and Oil Pipeline Prewarning System in Real Soil Environment
Fang Wang,
Jichuan Xing,
Jinxin Li,
Feng Zhao and
Shufeng Zhang
Mathematical Problems in Engineering, 2021, vol. 2021, 1-13
Abstract:
With the development of technology, the total extent of global pipeline transportation is also increased. However, the traditional long-distance optical fiber prewarning system has poor real-time performance and high false alarm rate when recognizing events threatening pipeline safety. The same vibration signal would vary greatly when collected in different soil environments and this problem would reduce the signal recognition accuracy of the prewarning system. In this paper, we studied this effect theoretically and analyzed soil vibration signals under different soil conditions. Then we studied the signal acquisition problem of long-distance gas and oil pipeline prewarning system in real soil environment. Ultimately, an improved high-intelligence method was proposed for optimization. This method is based on the real application environment, which is more suitable for the recognition of optical fiber vibration signals. Through experiments, the method yielded high recognition accuracy of above 95%. The results indicate that the method can significantly improve signal acquisition and recognition and has good adaptability and real-time performance in the real soil environment.
Date: 2021
References: Add references at CitEc
Citations:
Downloads: (external link)
http://downloads.hindawi.com/journals/MPE/2021/6673325.pdf (application/pdf)
http://downloads.hindawi.com/journals/MPE/2021/6673325.xml (text/xml)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:6673325
DOI: 10.1155/2021/6673325
Access Statistics for this article
More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().