[1]谭平a,陈冠帆a,黄楚媛b,等.基于SSA-BP补偿的电连接温度监测节点研究[J].浙江科技学院学报,2023,(05):430-438.[doi:10.3969/j.issn.1671-8798.2023.05.009]
 TAN Pinga,CHEN Guanfana,HUANG Chuyuanb,et al.Research on temperature monitoring node of electrical connection based on SSA-BP compensation[J].,2023,(05):430-438.[doi:10.3969/j.issn.1671-8798.2023.05.009]
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基于SSA-BP补偿的电连接温度监测节点研究(/HTML)
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《浙江科技学院学报》[ISSN:1001-3733/CN:61-1062/R]

卷:
期数:
2023年05期
页码:
430-438
栏目:
出版日期:
2023-10-31

文章信息/Info

Title:
Research on temperature monitoring node of electrical connection based on SSA-BP compensation
文章编号:
1671-8798(2023)05-0430-09
作者:
谭平1a陈冠帆1a黄楚媛1b丁进1a刘娟2
(1.浙江科技学院 a.自动化与电气工程学院; b.中德工程师学院,杭州 310023; 2.中铁高铁电气装备股份有限公司,陕西 宝鸡 721013)
Author(s):
TAN Ping1a CHEN Guanfan1a HUANG Chuyuan1b DING Jin1a LIU Juan2
(1a.School of Automation and Electrical Engineering; 1b.Chinese-German Institute of Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, Zhejiang, China; 2.China Railway High-Speed Electrification Equipment Corporation Limited, Bao
关键词:
接触网电连接温度监测无线传感网络SSA-BP神经网络
分类号:
U225.4
DOI:
10.3969/j.issn.1671-8798.2023.05.009
文献标志码:
A
摘要:
【目的】为了实时精确地监测接触网中电连接温度,设计了“Sub-GHz+GPRS/4G”无线传输技术温度监测节点。【方法】通过硬件选型、供电电路设计及低功耗休眠策略确保监测节点低功耗性能。将监测中心部署于云平台,汇聚网关数据进行数据的存储与分析,通过移动端或个人电脑实时观测电连接温度状态; 然后深入分析热敏电阻的非线性特性,采用麻雀搜索算法(sparrow search algorithm,SSA)优化反向传播(back propagation,BP)神经网络补偿采集数据,实现温度高精度测量。【结果】采用SSA-BP神经网络进行非线性补偿,其均方根误差和平均绝对误差分别为0.023 0 ℃和0.019 5 ℃; 在实际场景下,监测节点具有高精度、低功耗的优点,能稳定可靠地监测电连接温度。【结论】本研究结果对接触网中电连接温度监测工程具有一定的参考价值。

参考文献/References:

[1] 王大洋.高速铁路接触网横向电连接故障机理研究[D].成都:西南交通大学,2020.
[2] CHEN Y, SONG B, ZENG Y, et al. Fault diagnosis based on deep learning for current-carrying ring of catenary system in sustainable railway transportation[J].Applied Soft Computing,2021,100:106907.
[3] ALKAM F, LAHMER T. A robust method of the status monitoring of catenary poles installed along high-speed electrified train tracks[J].Results in Engineering,2021,12:100289.
[4] 李武云.接触网线夹温度的远程监测设计与实现[D].绵阳:西南科技大学,2019.
[5] CHEN K, YUE Y, TANG Y. Research on temperature monitoring method of cable on 10 kV railway power transmission lines based on distributed temperature sensor[J].Energies,2021,14(12):3705.
[6] CHEN Y, WANG S, HAO Y, et al. The 500 kV oil-filled submarine cable temperature monitoring system based on BOTDA distributed optical fiber sensing technology[C]//2020 International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence(ICSMD). Xi’an:IEEE,2020:180.
[7] DU C, DUTTA S, KURUP P, et al. A review of railway infrastructure monitoring using fiber optic sensors[J].Sensors and Actuators A:Physical,2020,303:111728.
[8] 涂冬明,谭平,李旭峰,等.红外热成像在电连接温度监测中的应用[J].浙江科技学院学报,2018,30(6):474.
[9] 刘云鹏,董王英,许自强,等.基于卷积神经网络的变压器套管故障红外图像识别方法[J].高压电器,2021,57(10):134.
[10] LIU T, LI G, GAO Y. Fault diagnosis method of substation equipment based on You Only Look Once algorithm and infrared imaging[J].Energy Reports,2022,8(supplement Ⅰ):171.
[11] 张友鹏,赵少翔,赵珊鹏,等.兰新高铁大风区接触网正馈线舞动在线监测系统设计[J].铁道学报,2021,43(7):57.
[12] 陈天宇,王思华,王宇,等.接触网感应式有电示警无线监测装置研究[J].仪表技术与传感器,2021(4):34.
[13] 邓志飞,鲍光海.基于超高频RFID技术的电缆接头温度在线监测系统[J].仪表技术与传感器,2021(7):71.
[14] FEI X, TIAN G Z. Optimization of communication network fault identification based on NB-IoT[J].Microprocessors and Microsystems,2021,80:103531.
[15] ABDULKAREM M, SAMSUDIN K, ROKHANI F Z, et al. Wireless sensor network for structural health monitoring:a contemporary review of technologies, challenges, and future direction[J].Structural Health Monitoring,2020,19(3):693.
[16] SUHERMAN S, FAHMI F, HERRY Z, et al. Sensor based versus server based image detection sensor using the 433 MHz radio link[C]//2020 4rd International Conference on Electrical, Telecommunication and Computer Engineering(ELTICOM). Medan:IEEE,2020:7.
[17] ABDUL B, MUHAMMAD Z, HYOUNGSUK Y. Compact and flexible wideband antenna for intraoral tongue-drive system for people with disabilities[J].IEEE Transactions on Antennas and Propagation,2020,68(3):2405.
[18] SCHWEIGER H G, MULTERER M, GORES H J. Fast multichannel precision thermometer[J].IEEE Transactions on Instrumentation and Measurement,2007,56(5):2002.
[19] NAVEEN K V, LAKSHMI N K V. Development of thermistor signal conditioning circuit using artificial neural networks[J].IET Science, Measurement & Technology,2015,9(8):955.
[20] FEDIN S, ZUBRETSKA I, POLIKARPOV O. Accuracy assurence of calibrated characteristics definition for NTC-Thermistors based on neural networks with radial basis functions[J].Metrology and Instruments,2017(1):37.
[21] XUE J, SHEN B. A novel swarm intelligence optimization approach:sparrow search algorithm[J].Systems Science & Control Engineering,2020,8(1):22.
[22] 刘栋,魏霞,王维庆,等.基于SSA-ELM的短期风电功率预测[J].智慧电力,2021,49(6):53.

备注/Memo

备注/Memo:
收稿日期:2022-08-23
基金项目:国家重点研发计划项目(2018YFB0606000); 国家自然科学基金项目(51677171,51577166,51827810)
通信作者:谭 平(1978— ),男,江苏省如皋人,教授,博士,主要从事智能安全系统研究。E-mail:115011@zust.edu.cn。
更新日期/Last Update: 2023-10-31