TY - JOUR N2 - 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. L1 - http://journals.pan.pl/Content/113106/PDF/12_MMS_4_INTERNET.pdf L2 - http://journals.pan.pl/Content/113106 PY - 2019 IS - No 4 EP - 755 DO - 10.24425/mms.2019.129587 KW - Buried Pipeline KW - Defect Recognition KW - Geomagnetic Anomaly Detection KW - Variational Mode Decomposition KW - Approximate Entropy A1 - Ju, Haiyang A1 - Wang, Xinhua A1 - Zhang, Tao A1 - Zhao, Yizhen A1 - Ullah, Zia PB - Polish Academy of Sciences Committee on Metrology and Scientific Instrumentation VL - vol. 26 DA - 2019.12.28 T1 - Defect recognition of buried pipeline based on approximate entropy and variational mode decomposition SP - 739 UR - http://journals.pan.pl/dlibra/publication/edition/113106 T2 - Metrology and Measurement Systems ER -