An Improved Method for Pipeline Leakage Localization With a Single Sensor Based on Modal Acoustic Emission and Empirical Mode Decomposition With Hilbert Transform

2020 ◽  
Vol 20 (10) ◽  
pp. 5480-5491 ◽  
Author(s):  
Changhang Xu ◽  
Shasha Du ◽  
Piao Gong ◽  
Zhenxing Li ◽  
Guoming Chen ◽  
...  
2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Ramtin Tabatabaei ◽  
Aref Aasi ◽  
Seyed Mohammad Jafari ◽  
Enrico Ciulli

Early detection of angular contact bearings, one of the important subsets of rolling element bearings (REBs), is critical for applications of high accuracy and high speed performance. In this study, acoustic emission (AE) method was applied to an experimental case with defects on angular contact bearing. AE signals were collected by AE sensors in different operating conditions. Signal to noise ratio (SNR) was calculated by kurtosis to entropy ratio (KER), then acquired signals were denoised by empirical mode decomposition (EMD) method, and optimal intrinsic mode function (IMF) was selected by the proposed method. Finally, envelope spectrum was applied to the denoised signals, and frequencies of defects were obtained in different rotating speeds, loadings, and defect sizes. For the first time, a small defect with width of 0.3 mm and loading of 475 N was detected in early stage of 0.04 KHz. Moreover, a comparison between theoretical and extracted defect frequencies suggested that our method successfully detected localized defects in both inner and outer race. Our results show promise in detecting small size defects in REBs.


Author(s):  
Yibo Li ◽  
Junlin Li ◽  
Liying Sun ◽  
Shijiu Jin ◽  
Shenghua Han

Corrosion in pipeline is a significant problem in the oil industry and there is also much interest in reducing leak due to corrosion. Correlation techniques are widely used in leak detection, and these have been extremely effective when attempting to locate leaks in metal pipes. Acoustic emission is a new non-destructive pipeline inspection technology which can be used to monitor crucial part of pipelines and detect pipe corrosion or leak in real time. However, AE signals causing by corrosion and leak are liable to noise interference on field. Aiming at solving the noise interference problems and increase the detection sensitivity and location accuracy of the leak, advanced signal analysis method based on Empirical Mode Decomposition were researched. Empirical Mode Decomposition is a great breakthrough in non-stable signal analysis and it decomposes the signals into a sum of finite intrinsic mode functions (IMF), which have real physical meaning. In the experiment, the leak signals from a 30 m pipeline were decomposed into 9 intrinsic mode functions by EMD, among which some IMF components containing typical AE characteristic can be selected to reconstruct the signal, and thus intrinsic characteristic of leak signal could be extracted and noise interference would be eliminated. Location accuracy of the leaking hole calculated with the reconstructed signals based on EMD algorithm was increased 64%.


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