1、发表论文
[45] j.zhang, l. peng, s. wen, s. huang. “a review on concrete structural properties and damage evolution monitoring techniques,” sensors, 2024, 24, 620: 1-29, doi: 10.3390/s24020620.
[44] h. sun, q. feng, j. li, f. zheng, l. peng, s. li, s. huang. “rail web buried defect location and quantification methods in hybrid high-order guided wave detection,” ieee transactions on instrumentation and measurement, 2024, 73: 1-12, doi: 10.1109/tim.2023.3338679.
[43] 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.
[42] 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.
[41] 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.
[40] 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.
[39] 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.
[38] 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.
[37] 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.
[36] 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.
[35] 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.
[34] 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.
[33] 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.
[32] 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.
[31] 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.
[30] 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.
[29] 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.
[28] 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.
[27] 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.
[26] 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.
[25] 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.
[24] 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.
[23] 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.
[22] 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.
[21] 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.
[20] 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.
[19] 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.
[18] 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.
[17] 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.
[16] 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.
[15] 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.
[14] 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.
[13] 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.
[12] 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.
[11] 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.
[10] 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.
[9] 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.
[8] 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.
[7] 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.
[6] 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.
[5] 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.
[4] 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.
[3] 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.
[2] 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.
[1] 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.
2、授权发明专利
[29] 黄松岭 王文志 赵伟 王珅 黄紫靖 宋小春 彭丽莎，device and method for testing steel defect based on internal and external magnetic perturbation，us 11,378,548 b2，2022.07.05，已授权。
[28] 黄松岭 王文志 赵伟 王珅 黄紫靖 宋小春 彭丽莎，钢材缺陷内外磁扰动综合检测装置及检测方法，zl 202010556179.4，2022.07.01，已授权。
[27] 黄松岭 彭丽莎 黄紫靖，管道螺旋焊缝漏磁自动识别方法和装置，zl 202011197381.9，2022.07.01，已授权。
[26] 黄松岭 彭丽莎 赵伟 王珅 邹军 汪芙平 龙跃 桂林 董甲瑞 于歆杰 黄紫靖，基于漏磁信号的缺陷轮廓反演方法，zl 20181035458 9.3，2021.01.01，已授权。
[25] 黄松岭 彭丽莎 赵伟 王珅 程迪 于佳，缺陷漏磁信号的单元伸缩构建方法，zl 201710174668.1，2020.06.19，已授权。
[24] 黄松岭 彭丽莎 赵伟 王珅 于歆杰 董甲瑞 汪芙平，一种基于深度-提离值变换的缺陷漏磁信号求解方法，zl 201710976832.0，2020.04.07，已授权。
[23] 黄松岭 彭丽莎 赵伟 王珅 李世松 邹军，基于法向分量的伪三维漏磁信号缺陷轮廓识别方法，zl 201710784842.4，2019.11.22，已授权。
[22] 黄松岭 彭丽莎 赵伟 王珅 龙跃，钢板缺陷磁旋阵成像检测方法及检测装置，zl 201710516071.0，2019.10.29，已授权。
[21] 黄松岭 彭丽莎 赵伟 张宇 王珅，缺陷漏磁信号垂直磁化方向单元组合求解方法，zl 201710252452.2，2019.07.26，已授权。
[20] 黄松岭 彭丽莎 赵伟 王珅 龙跃，基于素信号组合求解缺陷漏磁信号的方法，zl 201710681267.5，2019.11.22，已授权。
[19] 黄松岭 彭丽莎 赵伟 王珅 于歆杰 李世松，基于漏磁信号的垂直分量的缺陷轮廓识别方法及装置，zl 201710686539.0，2019.11.22，已授权。
[18] 黄松岭 赵伟 彭丽莎 王珅 程迪 董甲瑞，method for reconstructing defect，us 10,935,520 b2，2021.03.02，已授权。
[17] 黄松岭 赵伟 彭丽莎 王珅 程迪 董甲瑞，漏磁检测单元缺陷伸缩重构方法，zl 201710174666.2，2020.03.27，已授权。
[16] 黄松岭 赵伟 彭丽莎 于佳，沿磁化方向的单元组合缺陷漏磁信号计算方法，zl 201710252481.9，2019.07.02，已授权。
[15] 黄松岭 龙跃 彭丽莎 王珅 赵伟，管道内检测器三维跟踪方法和装置，zl 202010070214.1，2021.01.22，已授权。
[14] 黄松岭 龙跃 彭丽莎 王珅 赵伟，漏磁检测提离补偿和缺陷深度解析的方法及装置，zl 201911284632.4 ，2020.08.06，已授权。
[13] 黄松岭 王文志 彭丽莎 赵伟 王珅 张敬华，device and method for detecting defect contour with omnidectionally equal sensitivity based on magnetic excitation，us 11,150,311 b2，2021.10.19，已授权。
[12] 黄松岭 王文志 彭丽莎 赵伟 王珅 黄紫靖，磁激各向同性缺陷轮廓成像装置及成像方法，zl 201911280680.6，2021.12.14，已授权。
[11] 黄松岭 黄紫靖 王文志 彭丽莎 龙跃，钢材缺陷磁成像装置及方法，zl 202010646149.2，2022.08.16，已授权。
[10] 黄松岭 赵伟 王珅 彭丽莎 张宇于歆杰 邹军 桂林 汪芙平，high-precision imaging and detecting device for detecting small defect of pipeline by helical magnetic matrix，us 10,338,160 b2，2019.07.02，已授权。
[9] 黄松岭 龙跃 宋小春 彭丽莎 王珅 赵伟，漏磁检测探头姿态补偿方法及装置，zl 201911285985.6，2021.08.20，已授权。
[8] 黄松岭 赵伟 王珅 彭丽莎 张宇 于歆杰 邹军 桂林 汪芙平，用于管道微小缺陷检测的螺旋磁矩阵高精度成像检测装置，zl 201710517066.1，2021.04.27，已授权。
[7] 黄松岭 赵伟 王珅 丁睿 彭丽莎，铁磁性构件离线漏磁成像检测装置及方法，zl 201510660623.6，2018.05.29，已授权。
[6] 黄松岭 龙跃 赵伟 王珅 彭丽莎 宋小春，漏磁检测缺陷边沿识别的方法，zl 202010114747.5 ，2021.10.22，已授权。
[5] 黄松岭 赵伟 王珅 于歆杰 彭丽莎 邹军 汪芙平 董甲瑞 桂林 龙跃，电磁多场耦合缺陷综合检测评价方法及装置，zl 201810711896.2，2020.04.07，已授权。
[4] 黄松岭 孙洪宇 赵伟 王珅 彭丽莎 汪芙平 黄紫靖 董甲瑞，适用于铝板缺陷检测的sv超声体波单侧聚焦换能器，zl 201910496301.0，2020.11.03，已授权。
[3] 黄松岭 赵伟 王珅 于歆杰 彭丽莎 邹军 汪芙平 董甲瑞 桂林 龙跃，method and device for detecting and evaluating defect， us 11,099,156 b2，2021.08.24，已授权。
[2] 黄松岭 孙洪宇 黄紫靖 王珅 彭丽莎，海底管道超声导波全向聚焦声透镜柔性换能器及检测方法，zl 202010713397.4，2021.10.22，已授权。
[1] 黄松岭 赵伟 丁睿 张振宇 孙长安 聂长志 王珅 彭丽莎 李世松，铁轨缺陷的检测方法、检测系统及车辆，zl 201510784666.5，2018.06.19，已授权。
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