Electric Power ›› 2019, Vol. 52 ›› Issue (4): 104-110.DOI: 10.11930/j.issn.1004-9649.201808121
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ZHOU Ziqiang1, JI Yang2, SU Ye1, CAI Junyu1
Received:
2018-08-25
Revised:
2018-12-02
Online:
2019-04-05
Published:
2019-04-16
Supported by:
CLC Number:
ZHOU Ziqiang, JI Yang, SU Ye, CAI Junyu. A Hybrid Transfer Learning/CNN Algorithm for Cable Tunnel Rust Recognition[J]. Electric Power, 2019, 52(4): 104-110.
[1] | 丁文其, 袁森林, 高小庆, 等. 电力隧道超大直径顶管施工扰动特性研究[J]. 岩土力学, 2010, 31(9):2901-2906 DING Wenqi, YUAN Senlin, GAO Xiaoqing, et al. Research on construction disturbance characteristics caused by super large diameter pipe jacking in electric power tunnel[J]. Rock and Soil Mechanics, 2010, 31(9):2901-2906 |
[2] | 李俊光, 黄鑫, 杨小礼. 城市隧道下穿电缆隧道时的数值计算分析及变形沉降预测[J]. 铁道科学与工程学报, 2008, 5(1):68-71 LI Junguang, HUANG Xin, YANG Xiaoli. Numerical simulation and settlement prediction of subway locating under cable tunnels[J]. Journal of Railway Science and Engineering, 2008, 5(1):68-71 |
[3] | 吴春荣, 黄鑫, 李海峰. 细水雾灭火系统在电缆隧道中的应用研究[J]. 消防科学与技术, 2008, 27(9):662-665 WU Chunrong, HUANG Xin, LI Haifeng. Study on application of mist extinguishing system in cable tunnel[J]. Fire Science and Technology, 2008, 27(9):662-665 |
[4] | JULIER S J, UHIMANN J K. Unscented filtering and nonlinear estimation[J]. Proceedings of the IEEE, 2004, 92(3):401-422. |
[5] | JIANG B, SAMPLE A P, WISTORT R M, et al. Autonomous robotic monitoring of underground cable systems[C]//International Conference on Icar, IEEE, 2005:673-679. |
[6] | 姜芸, 付庄. 一种小型电缆隧道检测机器人设计[J]. 华东电力, 2009, 37(1):95-97 JIANG Yun, FU Zhuang. Design of pint-size cable tunnel inspecting robots[J]. East China Electric Power, 2009, 37(1):95-97 |
[7] | 谢振宇, 付庄, 宋国强, 等. 基于行为的电缆隧道综合检测机器人控制系统研究[J]. 机械与电子, 2008(4):47-51 XIE Zhenyu, FU Zhuang, SONG Guoqiang, et al. Control system research of behavior-based cable tunnel inspection robot[J]. Machinery & Electronics, 2008(4):47-51 |
[8] | 冯凌, 杨华夏, 魏东. 分体式电缆隧道检测机器人的移动结构研究[J]. 自动化仪表, 2017, 38(6):46-50 FENG Ling, YANG Huaxia, WEI Dong. Research on the moving structure of split cable tunnel inspection robot[J]. Process Automation Instrumentation, 2017, 38(6):46-50 |
[9] | DONG Z, LAI C S, QI D, et al. A general memristor-based pulse coupled neural network with variable linking coefficient for multi-focus image fusion[J]. Neurocomputing, 2018, 308:172-183. |
[10] | 张晴晴, 刘勇, 潘接林, 等. 基于卷积神经网络的连续语音识别[J]. 工程科学学报, 2015, 37(9):1212-1217 ZHANG Qingqing, LIU Yong, PAN Jielin, et al. Continuous speech recognition by convolutional neural networks[J]. Chinese Journal of Engineering, 2015, 37(9):1212-1217 |
[11] | HUBEL D H, WIESEL T N. Receptive fields, binocular interaction and functional architecture in the cat's visual cortex[J]. The Journal of Physiology, 1962, 160:106-154. |
[12] | LECUN Y, BOTTOU L, BENGIO Y, et al. Gradient-based learning applied to document recognition[J]. Proceedings of the IEEE, 1998, 86(11):2278-2324. |
[13] | ZHAO Z H, YANG S P, MA Z Q. License plate character recognition based on convolutional neural network LeNet-5[J]. Journal of System Simulation, 2010, 22(3):638-641. |
[14] | CIRESAN D C, MEIER U, GAMBARDELLA L M, et al. Convolutional neural network committees for handwritten character classification[C]//International Conference on Document Analysis and Recognition, IEEE, 2011:1135-1139. |
[15] | YUAN Z W, ZHANG J. Feature extraction and image retrieval based on AlexNet[C]//Eighth International Conference on Digital Image Processing, 2016. |
[16] | TSOUPOS A, KHADKIKAR V M. A novel SVM technique with enhanced output voltage quality for indirect matrix converters[J]. IEEE Transactions on Industrial Electronics, 2019, 66(2):832-841. |
[17] | XIAO Z, YE S J, ZHONG B, et al. BP neural network with rough set for short term load forecasting[J]. Expert Systems with Applications, 2009, 36(1):273-279. |
[18] | HUANG G B, ZHU Q Y, SIEW C K. Extreme learning machine:theory and applications[J]. Neurocomputing, 2006, 70(1-3):489-501. |
[19] | 逯彦秋, 安关峰, 程进. 基于主动导波的钢筋锈蚀识别技术[J]. 北京工业大学学报, 2014, 40(6):865-871 LU Yanqiu, AN Guanfeng, CHENG Jin. Technology of steel corrosion detection based on the guided wave testing[J]. Journal of Beijing University of Technology, 2014, 40(6):865-871 |
[20] | 赵新, 易伟建, 徐圣. 钢筋混凝土梁锈蚀损伤定位与识别[J]. 振动与冲击, 2007, 26(8):35-38 ZHAO Xin, YI Weijian, XU Sheng. Location and identification of corrosion of reinforced concrete beams[J]. Journal of Vibration and Shock, 2007, 26(8):35-38 |
[21] | PAN S J, YANG Q. A survey on transfer learning[J]. IEEE Transactions on Knowledge and Data Engineering, 2010, 22(10):1345-1359. |
[22] | ELFWING S, UCHIBE E, DOYA K. Sigmoid-weighted linear units for neural network function approximation in reinforcement learning[J]. Neural Networks, 2018, 107:3-11. |
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