Pipeline Leak Diagnosis Based on SDAE

To solve the problem that different oil and gas pipeline leakage signals are difficult to distinguish, a method of SDAE oil and gas pipeline leakage diagnosis was proposed. Firstly, the image preprocessing of one-dimensional signal is introduced to convert the original acoustic emission signal into...

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Bibliographic Details
Published in:2023 5th International Conference on Control and Robotics (ICCR) pp. 221 - 224
Main Authors: Lang, Xianming, Sui, Dongye, Lv, Yuanhao, Yuan, Kaixin, Zhang, He
Format: Conference Proceeding
Language:English
Published: IEEE 23.11.2023
Subjects:
Acoustic emission
Autoencoder
Feature extraction
Leakage diagnosis
Noise reduction
Oil and gas pipeline
Oils
Pipelines
Robots
Robustness
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Summary:To solve the problem that different oil and gas pipeline leakage signals are difficult to distinguish, a method of SDAE oil and gas pipeline leakage diagnosis was proposed. Firstly, the image preprocessing of one-dimensional signal is introduced to convert the original acoustic emission signal into two-dimensional feature gray map. Then, the feature extraction of two-dimensional feature gray image is carried out by the stack denoising autoencoder. Finally, the pipeline leakage diagnosis is carried out. The experimental results show that the method can accurately diagnose different types of pipeline leakage with an accuracy of 99.65%. Compared with one-dimensional original signal, the accuracy of two-dimensional gray image is improved by 27.72%. Compared with other methods, the accuracy of this method is improved by 3.08%. Compared with other methods, the superiority of this method in leakage diagnosis is further verified.
DOI:10.1109/ICCR60000.2023.10444746