External Breaking Vibration Identification Method of Transmission Line Tower Based on Solar-Powered RFID Sensor and CNN
| العنوان: | External Breaking Vibration Identification Method of Transmission Line Tower Based on Solar-Powered RFID Sensor and CNN |
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| المؤلفون: | Kaiyun Wen, Fangming Deng, Zhongxin Xie, Huafeng Liu, Jin Tong |
| المصدر: | Electronics, Vol 9, Iss 3, p 519 (2020) Electronics Volume 9 Issue 3 |
| بيانات النشر: | MDPI AG, 2020. |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | Power management, Computer Networks and Communications, Computer science, convolutional neural network, lcsh:TK7800-8360, tower vibration identification, 02 engineering and technology, 01 natural sciences, Relevance vector machine, Transmission line, 0202 electrical engineering, electronic engineering, information engineering, Electronic engineering, Radio-frequency identification, ComputerSystemsOrganization_SPECIAL-PURPOSEANDAPPLICATION-BASEDSYSTEMS, Electrical and Electronic Engineering, rfid sensor, business.industry, 020208 electrical & electronic engineering, 010401 analytical chemistry, lcsh:Electronics, 0104 chemical sciences, relevance vector machine, Vibration, Hardware and Architecture, Control and Systems Engineering, Signal Processing, business |
| الوصف: | This paper proposes an external breaking vibration identification method of transmission line tower based on a radio frequency identification (RFID) sensor and deep learning. The RFID sensor is designed to obtain the vibration signal of the transmission line tower. In order to achieve long-time monitoring and longer working distance, the proposed RFID sensor tag employs a photovoltaic cell combined with a super capacitor as the power management module. convolution neural network (CNN) is adopted to extract the characteristics of vibration signals and relevance vector machine (RVM) is then employed to achieve vibration pattern identification. Furthermore, the Softmax classifier and gradient descent method are used to adjust the weights and thresholds of CNN, so as to obtain a high-precision identification structure. The experiment results show that the minimum sensitivity of the proposed solar-powered RFID sensor tag is &minus 29 dBm and the discharge duration of the super capacitor is 63.35 h when the query frequencies are 5/min. The optimum batch size of CNN is 5, and the optimum number of convolution cores in the first layer and the second layer are 2 and 4, respectively. The maximum number of iterations is 10 times. The vibration identification accuracy of the proposed method is over 99% under three different conditions. |
| وصف الملف: | application/pdf |
| اللغة: | English |
| تدمد: | 2079-9292 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::af3e4e1bda3d98323038769fc670c8d8 https://www.mdpi.com/2079-9292/9/3/519 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....af3e4e1bda3d98323038769fc670c8d8 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 20799292 |
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