Quantitative Identification and Localization for Pipeline Microleakage by Fiber Distributed Acoustic Sensor
Baoqiang Yan, Hao Li, Keqing Zhang, Xiangpeng Xiao, Tao He, Cunzheng Fan, Zhijun Yan, Qizhen Sun
Abstract
Pipeline integrity management is of great significance for ensuring the safety of life and property. Due to the stable running, no pressure drops, and hidden characteristics, the identification and localization of microleakage remain a challenging task. To solve this problem, we propose a pipeline Leakage Noise Standard Deviation (LNSD) method based on the highly sensitive distributed acoustic sensing (DAS) system. As the sensing medium, the backscattering enhanced optical fiber (BEOF) is placed in a screw-like shape to form continuous distribution of acoustic sensors for quantitative identification and localization pipeline microleakage. The experimental results indicate that there is a well-fitted quadratic relationship between the standard deviation of the leakage induced noise and the leakage size, which is consistent with the theoretical analysis. The proposed method enables the detection of microleakage as small as 0.5 mm at a flow rate of 2.0 m/s, besides, the Leakage Identification Model (LIM) is constructed for the quantitative identification of various sizes with an identification error of 0.03 mm for microleakage size of 0.8 mm. Furthermore, the high-accuracy localization of microleakage is achieved by the continuous distribution of acoustic sensors with an error of 3.85 cm. The approach presented in this study enables non-invasive and highly sensitive online detection of pipeline microleakage, which will exhibit great potential for future pipeline integrity management.