Above-ground marker system of pipeline internal inspection instrument based on geophone array

被引:0
|
作者
Wu, Xiao [1 ,2 ]
Jin, Shi-Jiu [1 ]
Li, Yi-Bo [1 ]
Xiao, Yun-Kui [2 ]
Zhao, Hui-Min [2 ]
机构
[1] School of Precision Instrument and Opto-Electronics Engineering, Tianjin University, Tianjin 300072, China
[2] Department of Automotive Engineering, Academy of Military Transportation, Tianjin 300161, China
关键词
Neural networks - Feature extraction - Seismic waves - Seismology - Extraction - Inspection - Support vector machines;
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中图分类号
学科分类号
摘要
The above-ground marker (AGM) system is an important part of pipeline internal inspection instrument, which can significantly reduce the mileage error in petroleum pipeline default inspection by internal inspector and improve the location precision for pipeline defaults. A geophone array based AGM was proposed in this paper, aiming at solving the problem resulting from increasing depth of the pipeline. When the internal inspector moved inside pipeline, it would strike the welds on the inner-wall of the pipeline and generate seismic signals, which would be gathered by AGM with high sensitivity. As the features such as frequency and energy of the seismic signals varied with the targets, empirical mode decomposition (EMD) was used for feature extraction of the signals. Firstly, the signals were decomposed into several intrinsic mode functions (IMFs). Secondly, the normalized energy distribution of IMFs were computed and used as feature vectors of the signals. Finally, the artificial neural network based on support vector machine (SVM) was applied to pattern recognition of the seismic signals, in order to identify the effective signals and noise signals. The proposed AGM is proved to be effective by the simulated experiments, in which recognition accuracy of 93% was achieved.
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页码:553 / 558
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