[1] LIU X B, ZHANG H, XIA M Y et al. Mechanical response of buried polyethylene pipelines under excavation load during pavement construction[J]. Engineering Failure Analysis, 90, 355-370(2018).

[2] LAI H S, TUN N N, KIL S H et al. Effect of defects on the burst failure of butt fusion welded polyethylene pipes[J]. Journal of Mechanical Science and Technology, 30, 1973-1981(2016).

[3] ALESHIN N P, KOZLOV D M, MOGILNER L Y. Ultrasonic testing of welded joints in polyethylene pipe[J]. Russian Engineering Research, 41, 123-129(2021).

[4] ZHU Zhibin. Defect detection of polyethylene pipe hot melt joint based on continuous excitation infrared thermography technology[J]. Transactions of the China Welding Institution, 44-48(2018).

[5] SHAO Xiang, ZHANG Shenjun, WU Wendong. Application of radiographic detection in soldered joint of buried polyethylene pipes for gas[J]. Nondestructive Testing, 40, 35-37(2018).

[6] DANDAN Z, JIAOJIAO R, JIAN G et al. Nondestructive testing of bonding defects in multilayered ceramic matrix composites using THz time domain spectroscopy and imaging[J]. Composite Structures, 112624(2020).

[7] REN Jiaojiao, LI Lijuan, ZHANG Dandan et al. Multi-feature parameter neural network analysis technique based on terahertz nondestructive testing[J]. Journal of Photonics, 46, 0412002(2017).

[8] JANSEN C, WIETZKE S, WANG H et al. Terahertz spectroscopy on adhesive bonds[J]. Polymer Testing, 30, 150-154(2011).

[9] CHEN Qiang, WANG Qiang, GU Xiaohong et al. Inspection of aging and defects of poly-ethylene pipe joints based on THz-TDS[J]. Laser & Optoelectronics Progres, 56, 217-222(2019).

[10] PALKA N, PANOWICZ R, CHALIMONIUK M et al. Nondestructive evaluation of puncture region in polyethylene composite by terahertz and X-ray radiation[J]. Composites Part B: Engineering, 92, 315-325(2016).

[12] MARYAM S A, RYAN S, FEDAR S et al. Using machine learning to automate ultrasound-based classification of butt-fused joints in medium-density polyethylene gas pipes[J]. The Journal of the Acoustical Society of America, 150, 561-572(2021).

[13] WANG Henan, REN Jiaojiao, ZHANG Dandan et al. Glass fiber reinforced polymer terahertz feature enhancement and defect imaging based on continuous wavelet transform[J]. Acta Materiae Compositae Sinica, 38, 4190-4197(2021).

[14] ZHENG Li, LIU Chuang, REN Jiaojiao et al. Debonding defect identification method of multilayer bonded structure based on LDA-CPSO-SVM optimization[J]. Journal of Photonics, 50, 1212004(2021).

[15] BAUER M, HUSSUNG R, MMATHEIS C et al. Fast FMCW terahertz imaging for in-process defect detection in press sleeves for the paper industry and image evaluation with a machine learning approach[J]. Sensors, 21, 6569(2021).

[16] CHEN Qi. Robot offline programming technology and error analysis for terahertz intelligent detection system[D](2020).

[17] RAHMAN M, HARYONO A, KHOUSA M A. Microwave nondestructive evaluation of glass reinforced epoxy and high density polyethylene pipes[J]. Journal of Nondestructive Evaluation, 39, 26(2020).

[18] JUAN B, STE´PHANE M. Invariant scattering convolution networks[C], 35, 1872-1886(2013).

[19] LIU Hui, LI Yongkang, GAO Fang et al. Transmission line fault diagnosis based on wavelet scattering with BiLSTM[J]. Foreign Electronic Measurement Technology, 40, 165-172(2021).

[20] LIU Z, YU G, ZHANG O et al. Wavelet scattering transform for ECG beat classification[J]. Computational and Mathematical Methods in Medicine, 2020, 1-11(2020).

[21] CHENG Yanling, CHENG Lianglun, WU Heng et al. A method of terahertz spectrum material identifition based on wavelet coefficient graph[J]. Spectroscopy and Spectral Analysis, 41, 3665-3670(2021).

[22] LI Dan, WANG Manman, LIU Junde et al. Steel surface defect recongnition based on a lightweight convolutional neural network[J]. Chinese Journal of Scientific Instrument, 43, 240-248(2022).