(1)代表性论文 [1] Arbitrarily-oriented tunnel lining defects detection from Ground Penetrating Radar images using deep Convolutional Neural networks[J]. Automation in Construction, 2022, 133: 104044. (SCI: 7.7) [2] GPRI2Net: A Deep-Neural-Network-Based Ground Penetrating Radar Data Inversion and Object Identification Framework for Consecutive and Long Survey Lines[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60: 1-20. (SCI: 5.6) [3] Defects segmentation: Mapping the tunnel lining internal defects with the Ground Penetrating Radar data using convolutional neural network[J]. Construction and building materials, 2022, 319:125658. (SCI: 6.141) [4] An Unsupervised Clustering-Based Sectionalized Displacement Reconstruction Method for Smart Geogrids Integrated with Fiber Bragg Grating Sensors[J]. Construction and Building Materials, 2021, 286(1): 122924. (SCI: 4.419) [5] Deep Neural Network-Based Permittivity Inversions for Ground Penetrating Radar Data[J]. IEEE Sensors Journal, 2021, 21(6): 8172-8183. (SCI: 3.301) [6] Automatic Recognition of Highway Tunnel Defects Based on an Improved U-Net Model[J]. IEEE Sensors Journal, 2019, 19(23): 11413-11423. (SCI: 3.301) [7] In-situ and real-time measurement of single-lap-joint bonded area stress distribution based on FBG reflectance spectrum analyses and self-adaptive method[J]. Optik, 2017, 131: 302-311. (SCI: 2.443) [8] Low-Cost Plate-Type MOEMS Uniaxial Vibration Sensor Based on Metal Etching and Fiber Collimator Technique[J]. IEEE Sensors Journal, 2016, 16(12): 4816-4821. (SCI: 3.301) [9] Study of Three-Component FBG Vibration Sensor for Simultaneous Measurement of Vibration, Temperature, and Verticality[J]. Journal of Sensors. 2015,1-9. (SCI: 3.301) [10] Development and application of smart geogrid embedded with fiber Bragg grating sensors[J]. Journal of Sensors, 2015,1-10. (SCI: 3.301) (2)代表性著作 [1] 国家标准:道路施工与养护机械设备沥青混合料搅拌设备[S].(起草人) [2] 团体标准:岩土工程模型试验光纤光栅测试技术规程[S].(起草人) [3] 团体标准:隧道衬砌质量无损检测技术规程[S].(起草人) [4] 箱式变电站智能检测软件1.0[CP]. 著作权登记号: 2022SR0329801.(第一位) [5] 堤坝渗漏红外高精度智能识别软件V1.0[CP]. 著作权登记号: 2019SR0891355.(第一位) [6] 基于单纯形和改进遗传算法的微震定位软件V1.0 [CP]. 著作权登记号: 2018SR071196.(第一位) |