- Tytuł:
- Defect recognition of buried pipeline based on approximate entropy and variational mode decomposition
- Autorzy:
-
Ju, Haiyang
Wang, Xinhua
Zhang, Tao
Zhao, Yizhen
Ullah, Zia - Powiązania:
- https://bibliotekanauki.pl/articles/221572.pdf
- Data publikacji:
- 2019
- Wydawca:
- Polska Akademia Nauk. Czytelnia Czasopism PAN
- Tematy:
-
Buried Pipeline
Defect Recognition
Geomagnetic Anomaly Detection
Variational Mode Decomposition
Approximate Entropy - Opis:
- The study aimed to examine the use of Geomagnetic Anomaly Detection (GAD) to locate the buried ferromagnetic pipeline defects without exposing them. However, the accuracy of GAD is limited by the background noise. In the present work, we propose an approximate entropy noise suppression (AENS) method based on Variational Mode Decomposition (VMD) for detection of pipeline defects. The proposed method is capable of reconstructing the magnetic field signals and extracting weak anomaly signals that are submerged in the background noise, which was employed to construct an effective detector of anomalous signals. The internal parameters of VMD were optimized by the Scale–Space algorithm, and their anti-noise performance was compared. The results show that the proposed method can remove the background noise in high-noise background geomagnetic field environments. Experiments were carried out in our laboratory and evaluation results of inspection data were analysed; the feasibility of GAD is validated when used in the application to detection of buried pipeline defects.
- Źródło:
-
Metrology and Measurement Systems; 2019, 26, 4; 739-755
0860-8229 - Pojawia się w:
- Metrology and Measurement Systems
- Dostawca treści:
- Biblioteka Nauki
Artykuł