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 −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.
With the continuous development of rural construction, the rural standard of living has been significantly improved in recent years. The length of rural roads and the number of vehicles continued to increase. However, due to the lack of necessary lighting guidance equipment at night in countryside, in the recent years, there have been many traffic accidents at night, causing huge losses. The problems of night traffic safety in countryside have also become increasingly serious. Favorable economic development and construction need a stable social order and environment as guarantee. Especially for rural night driving, there are many contradictory problems in its development. In addition, there is not much research on this direction. Therefore, optimizing the night driving safety in countryside is of great significance for promoting the stand of rural economic development and social order. This paper takes rural night driving as the research object, by combining with the current rural road infrastructure planning and construction and the relationship between safety and existing energy and resources. The paper analyzes the practical problems of driving at night in rural areas of China, through the research and put forward the optimization measures of night driving safety in countryside.
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