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Acoustic emission (AE) based small leak detection of galvanized steel pipe due to loosening of screw thread connection

机译:由于螺纹连接松动,基于声发射(AE)的镀锌钢管小泄漏检测

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摘要

Galvanized steel pipes are widely used for indoor gas distribution. Leakage in the pipeline system is prone to occur in screw thread connection as opposed to tube itself. Early detection of small leak is of great significance to ensure the safety and comfort in doors. This work presents an experimental investigation on AE based small leak detection of galvanized steel pipe due to screw thread loosening. The waveform, frequency and energy signatures of the AE signals are first extracted and compared. Regarding the fact that the small leak signals lack obvious characteristics and are easily submerged in background noise, a pattern recognition method based on support vector machine (SVM) is employed for leak detection. Through training and testing on the experimental data, it is verified that the algorithm based on SVM with RBF kernel function is of the highest accuracy and efficiency with a 1.9% false alarm rate at most. (C) 2017 Elsevier Ltd. All rights reserved.
机译:镀锌钢管广泛用于室内气体分配。与管子本身相反,螺纹连接中容易发生管道系统泄漏。尽早发现小泄漏对确保门的安全性和舒适性具有重要意义。这项工作提出了对基于AE的由于螺纹松动引起的镀锌钢管小泄漏检测的实验研究。首先提取并比较AE信号的波形,频率和能量特征。针对小泄漏信号缺乏明显特征且容易淹没在背景噪声中的事实,采用基于支持向量机(SVM)的模式识别方法进行泄漏检测。通过对实验数据的训练和测试,验证了基于带有RBF核函数的SVM的算法具有最高的准确性和效率,虚警率最高为1.9%。 (C)2017 Elsevier Ltd.保留所有权利。

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