基于微型能量采集的無(wú)線傳感器網(wǎng)絡(luò)自供電與傳輸系統(tǒng)
[Abstract]:With the aggravation of energy crisis, energy acquisition technology develops rapidly. Meanwhile, in order to meet the needs of human economic and social development, the types and number of sensors in the Internet of things are increasing rapidly. Therefore, using energy acquisition technology and wireless sensor technology to create a "battery free" wireless sensor network has been the trend of the times. On the basis of deep research on various energy acquisition and conversion technologies and wireless sensor network technologies, this paper first analyzes the current research situation of this topic at home and abroad, and then expounds the principle of solar energy and temperature difference energy acquisition technology. Finally, the related hardware, software design and related application scene theory are explored. In this paper, an energy acquisition circuit for solar energy and thermal energy acquisition is designed, and a programmable power supply management circuit is designed in combination with practical application scenarios. The energy management efficiency of the power management circuit can reach 90% after testing. In order to fully guarantee the stability of the system, the ultra-low power wireless transceiver module is adopted in the design. In view of the dynamic nature of energy acquisition, the dynamic control of the signal transmitting frequency of the wireless transceiver module is realized by coding. The energy balance is realized. This paper also explores the optimal power allocation strategy for wireless channel time division based on dynamic energy acquisition. A mathematical model of wireless channel throughput under dynamic power constraints is established, and an improved water injection algorithm is proposed on the basis of which the research goal is achieved by testing the algorithm. The wireless video digest transmission scheme based on dynamic energy acquisition is also studied in this paper. Firstly, the video digest transmission model under dynamic energy acquisition is established, then the optimization strategy is adopted to optimize the model. Finally, the best video summary under energy acquisition is determined by bubbling method. The simulation results show that the algorithm has good convergence and the computational complexity is within a controllable range.
【學(xué)位授予單位】:天津大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2014
【分類號(hào)】:TP212.9;TN929.5
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