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L. Peng,S. Li, H. Sun and S. Huang. “A Pipe Ultrasonic Guided Wave Signal Generation Network Suitable for Data Enhancement in Deep Learning: US-WGAN,” Energies, 2022, 15(18): 6695, doi: 10.3390/en15186695.
L. Peng, S. Huang, S. Wang and W. Zhao, “A Simplified Lift-Off Correction for Three Components of the Magnetic Flux Leakage Signal for Defect Detection,” IEEE Transactions on Instrumentation and Measurement, 2021, 70: 1-9, doi: 10.1109/TIM. 2021.3058407.
L. Peng, S. Huang, S. Wang and W. Zhao, “An Element-Scaling-Revising Method (ESRM) for Magnetic Flux Leakage Signal Analysis,” International Journal of Applied Electromagnetics and Mechanics, 2018, 57(1): 83-92, doi: 10.3233/JAE-170128.
L. Peng, S. Huang, S. Wang and W. Zhao, “Data Recovery Method for MFL Signals Based on Sinc Function for Oil & Gas Pipeline,” IEEE Sensors 2020. 2020: 1-4, doi: 10.1109/SENSORS47125.2020.9278657.
L. Peng, S. Huang, S. Wang and W. Zhao, “Three-Dimensional Magnetic Flux Leakage Signal Analysis and Imaging Method for Tank Floor Defect,” The Journal of Engineering, 2018, 17: 1865-1870, doi: 10.1049/joe.2018.8344.
L. Peng, S. Huang, S. Wang and W. Zhao, “High Precision Identification Method of Fan Main Shaft Defects Based on Rotating Magnetic Field Detection,” IEEE International Instrumentation and Measurement Technology Conference, 2021:1-6, doi: 10.1109/I2MTC 50364.2021.9460043.
L. Peng, H. Sun, S. Wang, Q. Wang, W. Zhao and S. Huang, “Defect Detection and Identification of Point-Focusing Shear-Horizontal EMAT for Plate Inspection,” Conference on Precision Electromagnetic Measurements, 2020: 1-2, doi: 10.1109/CPEM49742.2020. 9191716.
L. Peng, S. Huang, S. Wang and W. Zhao, “An Element-Combination Method for Arbitrary Defect Reconstruction from MFL Signals,” IEEE International Instrumentation and Measurement Technology Conference, 2020: 1-6, doi: 10.1109/I2MTC 43012.2020.9128671.
L. Peng, S. Huang, S. Wang and W. Zhao, “A Simplified Calculation Model of MFL Signal of Defect Based on Lift-off Value,” Conference on Precision Electromagnetic Measurements, 2020: 1-2, doi: 10.1109/CPEM49742.2020.9191696.
L. Peng, S. Huang, S. Wang and W. Zhao, “A 3-D Pseudo Magnetic Flux Leakage (PMFL) Signal Processing Technique for Defect Imaging,” IEEE International Instrumentation and Measurement Technology Conference, Auckland, New Zealand, 2019: 1-5, doi: 10.1109/I2MTC.2019.8827047.
L. Peng, S. Huang, Q. Wang, S. Wang and W. Zhao, “A Lift-Off Revision Method for Magnetic Flux Leakage Measurement Signal,” Conference on Precision Electromagnetic Measurements, Paris, 2018: 1-2, doi: 10.1109/I2MTC.2018.8409535.
L. Peng, S. Huang, S. Wang and W. Zhao, “The Real-Time Quantitation and Display Method for Incomplete Defect MFL Signals,” 19th World Conference on Non-Destructive Testing, WCNDT 2016: 1-10.
S. Huang, L. Peng, H. Sun, Q. Wang, W. Zhao and S. Wang, “Frequency Response of an Underwater Acoustic Focusing Composite Lens,” Applied Acoustics, 2021, 173: 1-6, doi: 10.1016/j.apacoust.2020.107692.
S. Huang, L. Peng, Q. Wang, S. Wang and W. Zhao, “An Opening Profile Recognition Method for Magnetic Flux Leakage Signals of Defect,” IEEE Transactions on Instrumentation and Measurement, 2019: 68(6): 2229-2236, doi: 10.1109/TIM. 2018.2869438.
S. Huang, L. Peng, S. Wang and W. Zhao, “A Basic Signal Analysis Approach for Magnetic Flux Leakage Response,” IEEE Transactions on Magnetics, 2018, 54(10): 1-6, doi: 10.1109/TMAG.2018.2858201.
S. Huang, L. Peng, Q. Wang, S. Wang and W. Zhao, “A Defect Opening Profile Estimation Method Based on the Right-Angle Characteristic of Vertical Component of MFL Signal,” Conference on Precision Electromagnetic Measurements, 2018: 1-5, doi: 10.1109/CPEM.2018.8500976.
H. Sun, L. Peng, J. Lin, S. Wang, W. Zhao and S. Huang, “Microcrack defect quantification using a focusing high-order SH guided wave EMAT: the physics-informed deep neural network GuwNet,” IEEE Transactions on Industrial Informatics, 2022, 18(5):3235-3247, doi: 10.1109/TII.2021.3105537.
H. Sun, L. Peng, S. Huang, S. Li, Y. Long, S, Wang, W. Zhao, “Development of a Physics-Informed Doubly Fed Cross-Residual Deep Neural Network for High-Precision Magnetic Flux Leakage Defect Size Estimation,” IEEE Transactions on Industrial Informatics, 2022, 18(3): 1629-1640, doi: 10.1109/TII.2021.3089333.
H. Sun, L. Peng, S. Wang, Q. Wang, W. Zhao and S. Huang, “Effective Focal Area Dimension Optimization of Shear Horizontal Point-Focusing EMAT Using Orthogonal Test Method,” IEEE Transactions on Instrumentation and Measurement, 2021, 70: 1-8, doi: 10.1109/TIM.2021.3073713.
H. Sun, L. Peng, S. Wang, S. Huang and K. Qu, “Development of Frequency-Mixed Point-Focusing Shear Horizontal Guided-Wave EMAT for Defect Inspection Using Deep Neural Network,” IEEE Transactions on Instrumentation and Measurement, 2021, 70: 1-14, doi: 10.1109/TIM.2020.3033941.
H. Sun, L. Peng, S. Huang, Q. Wang, S. Wang and W. Zhao, “Analytical Model and Optimal Focal Position Selection for Oblique Point-Focusing Shear Horizontal Guided Wave EMAT,” Construction and Building Materials, 2020: 258: 1-8, doi: 10.1016/j. conbuildmat.2020.120375.
H. Sun, L. Peng, S. Huang, S. Wang, Q. Wang and W. Zhao, “Mode Identification of Denoised SH Guided Waves Using Variational Mode Decomposition Method,” IEEE Sensors 2020. 2020: 1-3, doi: 10.1109/SENSORS47125.2020.9278659.
H. Sun, L. Peng, S. Wang, Q. Wang, W. Zhao and S. Huang, “Effective Focal Area Dimension Optimization of Shear-Horizontal Point-Focusing EMAT Using Orthogonal Test Method,” Conference on Precision Electromagnetic Measurements, 2020: 1-2, doi: 10.1109/CPEM49742.2020.9191861s.
S. Huang, H. Sun, L. Peng, S. Wang, Q. Wang and W. Zhao, “Defect Detection and Identification of Point-Focusing Shear-Horizontal EMAT for Plate Inspection,” IEEE Transactions on Instrumentation and Measurement, 2021, 70: 1-9, doi: 10.1109/TIM.2021.3062421.
Y. Long, S. Huang, L. Peng, S. Wang and W. Zhao, “A Novel Compensation Method of Probe Gesture for Magnetic Flux Leakage Testing,” IEEE Sensors Journal, 2021, 21(9): 10854-10863, doi: 10.1109/JSEN.2021.3059899.
Y. Long, S. Huang, L. Peng, S. Wang and W. Zhao, “A Characteristic Approximation Approach to Defect Opening Profile Recognition in Magnetic Flux Leakage Detection,” IEEE Transactions on Instrumentation and Measurement, 2021: 70: 1-12, doi: 10.1109/TIM.2021.3050185.
Y. Long, S. Huang, L. Peng, W. Wang, S. Wang and W. Zhao, “Internal and External Defects Discrimination of Pipelines Using Composite Magnetic Flux Leakage Detection,” IEEE International Instrumentation and Measurement Technology Conference, 2021: 1-6, doi: 10.1109/I2MTC50364.2021.9460069.
Y. Long, S. Huang, L. Peng, S. Wang and W. Zhao, “A New Dual Magnetic Sensor Probe for Lift-off Compensation in Magnetic Flux Leakage Detection,” IEEE International Instrumentation and Measurement Technology Conference, 2020: 1-6, doi: 10.1109/I2MTC43012.2020.9129204.
Y. Long, S. Huang, L. Peng, S. Wang and W. Zhao, “A Characteristic Approximation Approach to Defect Edge Detection in Magnetic Flux Leakage Testing,” Conference on Precision Electromagnetic Measurements, 2020: 1-2, doi: 10.1109/ CPEM49742.2020.9191752.
W. Wang, S. Huang, L. Peng, Y. Long, S. Wang and W. Zhao, “An Improved MFL Method Fusing Multi-Space Magnetic Field Information for The Surface Defect Inspecting,” IEEE International Instrumentation and Measurement Technology Conference, 2021, pp. 1-6, doi: 10.1109/I2MTC50364.2021.9460085.
W. Wang, S. Huang, L. Peng, S. Wang and W. Zhao, “Identifying Surface Defect Opening Profiles Based on the Uniform Magnetic Field Distortion,” IEEE International Instrumentation and Measurement Technology Conference, 2020: 1-6, doi: 10.1109/I2MTC43012.2020.9129184.
Y. Long, J. Zhang, S. Huang, L. Peng, W. Wang, S. Wang, W. Zhao, "A Novel Crack Quantification Method for Ultra-High-Definition Magnetic Flux Leakage Detection in Pipeline Inspection," IEEE Sensors Journal, 2022, 22(16): 16402-16413, doi: 10.1109/JSEN.2022.3190684.
H. Sun, S. Wang, S. Huang, L. Peng, Q. Wang and W. Zhao, “Design and Characterization of an Acoustic Composite Lens With High-Intensity and Directionally Controllable Focusing,” Scientific Reports, 2020, 10: 1469, doi: 10.1038/s41598-020-58092-6.
H. Sun, S. Wang, S. Huang, L. Peng, Q. Wang, W. Zhao and Jun Zou, “Point-Focusing Shear-Horizontal Guided Wave EMAT Optimization Method Using Orthogonal Test Theory,” IEEE Sensors Journal, 2020, 20(12): 6295-6304, doi: 10.1109/ JSEN.2020.2976198.
H. Sun, S. Wang, S. Huang, L. Peng, Q. Wang and W. Zhao, “Oblique Point-Focusing Shear-Horizontal Guided-Wave Electromagnetic Acoustic Transducer with Variable PPM Spacing,” IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 2020, 67(8): 1691-1700, doi: 10.1109/TUFFC.2020.2980621.
H. Sun, S. Wang, S. Huang, L. Peng, Q. Wang and W. Zhao, “3D Focusing Acoustic Lens Optimization Method Using Multi-Factor and Multi-Level Orthogonal Test Designing Theory,” Applied Acoustics, 2020, 170: 107538, doi: 10.1016/j.apacoust. 2020.107538.
S. Wang, S. Huang, Q. Wang, L. Peng and W. Zhao, “Accelerated Optimizations of an Electromagnetic Acoustic Transducer With Artificial Neural Networks as Metamodels,” Journal of Sensors an Sensor Systems, 2017, 6(2): 269-284, doi: 10.5194/jsss-6-269-2017.
S. Huang, H. Sun, S. Wang, K. Qu, W. Zhao and L. Peng, “SSWT and VMD Linked Mode Identification and Time-of-Flight Extraction of Denoised SH Guided Waves,” IEEE Sensors Journal, 2021, 21(13): 14709-14717, doi: 10.1109/JSEN.2021.3051658.
缪立恒, 潘峰, 彭丽莎, 黄松岭. 基于漏磁信号深度特性的缺陷深度轮廓迭代优化方法. 中国电机工程学报, 2022, 42(8): 3077-3086, doi: 10.13334/j.0258-8013.pcsee.211252.
黄松岭, 彭丽莎, 赵伟, 王珅.缺陷漏磁成像技术综述. 电工技术学报, 2016, 31(20): 55-63, doi: 10.19595/j.cnki.1000-6753.tces. 2016.20.005.
彭丽莎, 王珅, 刘欢, 黄松岭, 赵伟. 漏磁图像的改进灰度级—彩色变换法. 清华大学学报(自然科学版), 2015, 55(5): 592-596, doi: 10.16511/j.cnki.qhdxxb.2015.05.018.
彭丽莎, 黄松岭, 赵伟, 王珅. 漏磁检测中的缺陷重构方法. 电测与仪表, 2015, 52(13): 1-6; 30.
黄松岭, 彭丽莎, 赵伟, 王珅. 无损检测中的缺陷漏磁成像技术.远东无损检测新技术论坛论文集, 2015: 347-354.