Nondestructive Test for Oil-well Tubing Defects Based on Neural Network and Multi-sensor Fusion

被引:0
|
作者
Wang Xiao [1 ]
Li Guohong [1 ]
机构
[1] N China Inst Aerosp Engn, Langfang, Hebei, Peoples R China
关键词
Neural network; Multi-sensor Fusion; Defects of Oil-well Tubing; Nondestructive Test; MAGNETIC-FLUX LEAKAGE;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper provides the method of nondestructive test for oil-well tubing detects based on neural network and multi-sensor fusion. Oil-well tubing magnetism of leak signal with defects is gathered, and its characteristic quantities are analyzed in the experiment. Oil-well tubing defect detecting model, which is applied to detect the oil-well tubing defects, is built up by establishing a group of characteristic quantities reflecting the defects sizes and utilizes neural network to map the nonlinear connection of signal characteristic quantities and defects sizes. It adopts the different characteristic quantities and fusion arithmetic according to the different defects, and processes the flaws and orifices defect detecting experiments based on characteristic quantities and data fusion arithmetic of neural network.
引用
收藏
页码:1496 / 1499
页数:4
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