QIU Xiufen, ZHANG Feng, SUN Zhiwei, JIA Qingsheng, LI Ming, SONG Cong, HE Changbang. A combined detection method for oil and gas pipeline damage based on distributed optical fiber sensing technology[J]. Oil & Gas Storage and Transportation, 2021, 40(8): 888-894. DOI: 10.6047/j.issn.1000-8241.2021.08.008
Citation: QIU Xiufen, ZHANG Feng, SUN Zhiwei, JIA Qingsheng, LI Ming, SONG Cong, HE Changbang. A combined detection method for oil and gas pipeline damage based on distributed optical fiber sensing technology[J]. Oil & Gas Storage and Transportation, 2021, 40(8): 888-894. DOI: 10.6047/j.issn.1000-8241.2021.08.008

A combined detection method for oil and gas pipeline damage based on distributed optical fiber sensing technology

  • The existing detection methods for third-party damage of the oil and gas pipelines are low efficient and easy to be disturbed by the external conditions such as the environmental magnetic field, which brings about a high false alarm rate. In order to improve the detection rate, a damage signal detection method for oil and gas pipelines based on the distributed optical fiber sensing technology was proposed. For the method, the short-time energy and the corrected zero crossing rate of each frame of signal in the detection period should be calculated at first, then the short-time average energy and the standard deviation of the corrected crossing rate of all frames of signal should be computed, and finally, the two should be combined together to determine if there is any damage signal, which could detect the pipeline damage signal effectively, further significantly reducing the false alarm rate of the pipeline detection system. By simulating various artificial and mechanical damage signals respectively, the feasibility and effectiveness of the new combined detection method were verified. The results show that the method of detecting the pipeline damage signals in combination with the short-time average energy and the corrected zero crossing rate can eliminate the interference, of which the detection accuracy for simulated artificial and mechanical intrusion events is more than 90%, capable of providing technical guarantee to the safe operation of pipelines.
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