| 基于神经网络的超声导波管道缺陷识别 |
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| 引用本文： | 赵彩萍,王维斌,何存富,吴斌.基于神经网络的超声导波管道缺陷识别[J].传感器与微系统,2009,28(11). |
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| 作者姓名： | 赵彩萍 王维斌 何存富 吴斌 |
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| 作者单位： | 1. 北京工业大学机电学院,北京,100124
2. 中国石油管道研究中心,河北,廊坊,065000 |
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| 摘 要： | 在役石油管道的腐蚀是造成石油管线运输故障的重要原因,适时检测在役管道是否被腐蚀至关重要。研究了超声导波进行长距离在役管道检测技术,并利用人工神经网络进行管道缺陷的智能识别,通过超声导波设备进行了管道缺陷检测实验,从原始检测数据的信号处理结果中提取出了样本特征值,并建立和训练了一种用于实现管道缺陷识别的BP神经网络。实验表明:使用该网络可进行超声导波管道缺陷的自动识别。
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| 关 键 词： | 超声导波 特征提取 神经网络 |
Defect recognition in pipes based on neural networks with ultrasonic guided waves |
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| ZHAO Cai-ping,WANG Wei-bin,HE Cun-fu,WU Bin.Defect recognition in pipes based on neural networks with ultrasonic guided waves[J].Transducer and Microsystem Technology,2009,28(11). |
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| Authors: | ZHAO Cai-ping WANG Wei-bin HE Cun-fu WU Bin |
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| Affiliation: | ZHAO Cai-ping1,WANG Wei-bin2,HE Cun-fu1,WU Bin1(1.College of Mechanical Engineer , Applied Electronics Technology,Beijing University of Technology,Beijing 100124,China,2.Petro China Pipeline Research Center,Langfang 065000,China) |
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| Abstract: | In-service pipeline corrosion is an important reason for failure of oil pipeline transport.Timely detection of corrosion of pipes in service is essential.Ultrasonic guided waves are used for long-distance pipeline inspection,and the artificial neural networks are used for intelligent recognition of pipeline defects.Pipes defect detection experiments are performed by the ultrasonic guided wave detection equipments.Based on the original detection signal,signal processing is performed,from the result of which ... |
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| Keywords: | ultrasonic guided wave feature extraction neural networks |
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