[1] 偶国富, 许根富, 朱祖超, 等. 弯管冲蚀失效流固耦合机理及数值模拟[J]. 机械工程学报, 2009, 45(11):119-124. OU Guofu, XU Genfu, ZHU Zuchao, et al. Fluid-structure interaction mechanism and numerical simulation of elbow erosion failure[J]. Journal of Mechanical Engineering, 2009, 45(11):119-124. [2] 周建民, 徐清瑶, 李鹏, 等. 钢轨无损检测中的超声导波技术[J]. 仪表技术与传感器, 2015(6):99-102. ZHOU Jianmin, XU Qingyao, LI Peng, et al. Ultrasonic guided wave technique for nondestructive testing of rails[J]. Instrument Technique and Sensor, 2015(6):99-102. [3] 周邵萍, 张蒲根, 吕文超, 等. 基于导波的弯管裂纹缺陷的检测[J]. 机械工程学报, 2015, 51(6):58-65. ZHOU Shaoping, ZHANG Pugen, LÜ Wenchao, et al. Detection of cracks in elbow pipes using guided waves[J]. Journal of Mechanical Engineering, 2015, 51(6):58-65. [4] HAYASHI T, KAWASHIMA K, SUN Zongqi, et al. Guided wave propagation mechanics across a pipe elbow[J]. Pressure Vessel Technology, 2005, 127(3):322-327. [5] BAKKALI M E. Guided wave propagation and scattering in pipeworks comprising elbows[J]. AIP Conference Proceedings, 2015, 1581(1):DOI:10.1063/1.4864838. [6] DEMMA A, CAWLEY P, LOWE M, et al. The effect of bends on the propagation of guided waves in pipes[J]. Journal of Pressure Vessel Technology, 2005, 127(3):328-335. [7] 裴洪, 胡昌华, 司小胜, 等. 基于机器学习的设备剩余寿命预测方法综述[J]. 机械工程学报, 2019, 55(8):1-13. PEI Hong, HU Changhua, SI Xiaosheng, et al. Review of machine learning based remaining useful life prediction methods for equipment[J]. Journal of Mechanical Engineering, 2019, 55(8):1-13. [8] 邹宁波, 谌海云, 刘全利, 等. 基于T(0, 1)模态超声导波的输气管道腐蚀检测[J]. 无损检测, 2013, 35(9):19-22. ZOU Ningbo, CHEN Haiyun, LIU Quanli, et al. Detection of gas transmission pipeline corrosion using ultrasonic guided waves of T(0, 1) mode[J]. Nondestructive Testing, 2013, 35(9):19-22. [9] QI Minxin, ZHOU Shaoping, NI Jing, et al. Investigation on ultrasonic guided waves propagation in elbow pipe[J]. International Journal of Pressure Vessels and Piping, 2016, (139-140):250-255. [10] QIU Lei, YUAN Shenfang, CHANG F K, et al. On-line updating Gaussian mixture model for aircraft wing spar damage evaluation under time-varying boundary condition[J]. Smart Materials and Structures, 2014, 23(12):125001. [11] TORKAMANI S, ROY S, BARKEY M E, et al. A novel damage index for damage identification using guided waves with application in laminated composites[J]. Smart Materials and Structures, 2014, 23(9):095015. [12] 殷书彦. 基于BP神经网络的手机病毒检测方法研[D]. 沈阳:沈阳师范大学, 2016. YIN Shuyan. Mobile phone virus detection method based on BP neural network[D]. Shenyang:Shenyang Normal University, 2016. [13] ZUR R M, JIANG Y, PESCE L L, et al. Noise injection for training artificial neural networks:A comparison with weight decay and early stopping[J]. Medical Physics, 2009, 36(10):4810-4818. [14] LAROCHELLE H, BENGIO Y, LOURADOUR J, et al. Exploring strategies for training deep neural networks[J]. Journal of Machine Learning Research, 2009, 1(10):1-40. [15] 韩力群. 人工神经网络教程[M]. 北京:北京邮电大学出版社, 2006. HANG Liqun. Artificial neural network course[M]. Beijing:Beijing University of Posts and Telecommunications Press, 2016. [16] 张清良, 李先明. 一种确定神经网络隐层节点数的新方法[J]. 吉首大学学报, 2002(1):91-93. ZHANG Qingliang, LI Xianming. A new method to determine the number of hidden nodes in neural network[J]. Journal of Jishou University, 2002(1):91-93. [17] 王建梅, 覃文忠. 基于L-M算法的BP神经网络分类器[J]. 武汉大学学报, 2005(10):85-88. WANG Jianmei, QIN Wenzhong. BP neural network classifier based on L-M algorithm[J]. Geomatics and Information Science of Wuhan University, 2005(10):85-88. [18] CORTES C, VAPNIK V. Support-vector networks[J]. Machine Learning, 1995, 20(3):273-297. [19] BAESENS B. An empirical assessment of kernel type performance for least squares support vector machine classifiers[C]//Fourth International Conference on Knowledge-Based Intelligent Information Engineering Systems & Allied Technologies, KES 2000, Brighton, UK, 2000, August 30-September 1. IEEE, 2000:313-316. |