电子测量与仪器学报

李振鹏,董明利,于明鑫,孟凡勇,张羽飞.Encoder-Decoder LSTM 网络的输电母排触点温度预测方法[J].电子测量与仪器学报,2022,36(4):32-39

Encoder-Decoder LSTM 网络的输电母排触点温度预测方法

Transmission busbar contact temperature prediction methodfor Encoder-Decoder LSTM networks

DOI：

英文关键词:electric power equipment temperature forecast deep learning optical fiber temperature measurement

基金项目:国家自然科学基金（51675053）项目资助

作者	单位
李振鹏	1. 北京信息科技大学光电测试技术及仪器教育部重点实验室,2. 北京信息科技大学光纤传感与系统北京实验室
董明利	1. 北京信息科技大学光电测试技术及仪器教育部重点实验室,2. 北京信息科技大学光纤传感与系统北京实验室
于明鑫	1. 北京信息科技大学光电测试技术及仪器教育部重点实验室,2. 北京信息科技大学光纤传感与系统北京实验室
孟凡勇	1. 北京信息科技大学光电测试技术及仪器教育部重点实验室,2. 北京信息科技大学光纤传感与系统北京实验室
张羽飞	1. 北京信息科技大学光电测试技术及仪器教育部重点实验室,2. 北京信息科技大学光纤传感与系统北京实验室

Author	Institution
Li Zhenpeng	1. Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science & Technology University,2. Beijing Laboratory of Optical Fiber Sensing and System, Beijing Information Science & Technology University
Dong Mingli	1. Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science & Technology University,2. Beijing Laboratory of Optical Fiber Sensing and System, Beijing Information Science & Technology University
Yu Mingxin	1. Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science & Technology University,2. Beijing Laboratory of Optical Fiber Sensing and System, Beijing Information Science & Technology University
Meng Fanyong	1. Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science & Technology University,2. Beijing Laboratory of Optical Fiber Sensing and System, Beijing Information Science & Technology University
Zhang Yufei	1. Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science & Technology University,2. Beijing Laboratory of Optical Fiber Sensing and System, Beijing Information Science & Technology University

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中文摘要:

机场行李传送装置输电母排触点状态的观测,对减少机场行李传送装置意外停机、保障机场正常运营具有重要的意义。输电母排触点故障发生时往往伴随温度的上升,温度的变化能够直观反映输电母排触点状态。因此可以采用编码器-解码器长短期记忆网络(Encoder-Decoder LSTM)对输电母排触点进行温度预测。首先采用双向长短期记忆网络(Bi-LSTM)组成的编码器对母排触点的历史温度数据进行编码,再由长短期记忆网络(LSTM)组成的解码器预测输出输电母排触点未来一段时间的温度值。通过对国内某机场行李传送装置一个月的温度观测数据进行测试。实验结果表明采用 Encoder-Decoder LSTM 的时间序列预测方法优于传统的时间序列预测模型以及其他现有的深度学习预测模型。

英文摘要:

The observation of transmission busbar contact status of airport baggage transfer device is of great significance to reduce the unplanned stoppage of airport baggage transfer device and ensure the normal operation of airport. The temperature change can visually reflect the status of the transmission busbar contact, which is often accompanied by the rise of temperature when the transmission busbar contact failure occurs. Therefore, Encoder-Decoder LSTM can be used to predict the temperature of transmission bus contacts. First, an encoder composed of a bi-directional long and short-term memory network (Bi-LSTM) is used to encode the historical temperature data of the busbar contacts, then a decoder composed of a long and short-term memory network (LSTM) is used to predict the temperature value of the transmission busbar contacts for a future period. One month of temperature observation data of a domestic airport baggage conveyor is tested. The experimental results show that the time series prediction method using Encoder-Decoder LSTM outperforms the traditional time series prediction model as well as other existing deep learning prediction models.

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