本文選題：電廠鍋爐 + ZigBee��； 參考：《東北電力大學》2017年碩士論文

【摘要】：智能電網(wǎng)逐步向著“四網(wǎng)融合”信息體系方向邁進,使得其對供電設備的穩(wěn)定性要求逐步提高,電廠鍋爐作為電網(wǎng)中制造電力的主導設備,其安全運作為電力的穩(wěn)定供給提供了保障。由于鍋爐相關設備使用時間長、體積大不易更換,導致了鍋爐泄漏事故的頻繁發(fā)生,為解決傳統(tǒng)有線監(jiān)測方式下布線困難、高溫使線路提前老化等問題,本文設計了一種基于ZigBee的電廠鍋爐氣體泄漏在線監(jiān)測系統(tǒng)。該系統(tǒng)利用ZigBee短距離無線通信技術代替有線方式,完成對電廠鍋爐的在線監(jiān)測。主要研究工作如下:(1)對ZigBee技術運用于系統(tǒng)的可行性深入分析,確定了系統(tǒng)的無線傳感器網(wǎng)絡拓撲結構。在此基礎上進行了總體架構設計以及各核心部分的軟硬件設計,硬件模塊電路主要包括傳感器模塊、路由器模塊和協(xié)調器模塊,具體完成對數(shù)據(jù)處理電路、天線電路、傳感器相關電路、SD卡外圍電路和電源模塊等電路的設計;軟件設計負責完成傳感器節(jié)點程序設計、路由器節(jié)點程序設計、協(xié)調器節(jié)點程序設計以及監(jiān)測中心軟件的設計。(2)對氣體泄漏數(shù)據(jù)進行分析挖掘,給出電廠鍋爐泄漏狀態(tài)評估算法(均權灰靶理論、熵權灰靶理論)步驟,并在此基礎上結合層次分析法提出層次熵權灰靶理論,完成對電廠鍋爐氣體泄漏狀態(tài)評估等級的劃分,有效地解決在沒有標準故障模型的情況下鍋爐泄漏狀態(tài)識別的問題,為鍋爐泄漏狀態(tài)評估提供了一種新途徑。(3)利用灰色GM(1,1)模型預測下一時間段內的氣體泄漏濃度數(shù)據(jù),最后得出預測值與實際值兩者的相對誤差小于8.5%,平均相對誤差控制在3.5%內。應用研究表明,系統(tǒng)測試穩(wěn)定性高,引入灰色系統(tǒng)理論將為電廠鍋爐的泄漏狀態(tài)評估和氣體泄漏預測提供了有力的理論支持,為電廠鍋爐的安全、穩(wěn)定及高效運行提供了保障。
[Abstract]:The smart grid is gradually moving towards the direction of "four networks fusion" information system, which makes the stability of power supply equipment improve gradually. Power plant boiler is the leading equipment in power grid. Its safe operation provides the guarantee for the stable supply of electric power. Because of the long time of boiler related equipment, the large volume is not easy to replace, which leads to the frequent occurrence of boiler leakage accident, in order to solve the problem of wiring under the traditional wired monitoring mode, the high temperature makes the line aging ahead of schedule, and so on. An on-line monitoring system of boiler gas leakage in power plant based on ZigBee is designed in this paper. In this system, ZigBee short range wireless communication technology is used instead of wired mode to complete the on-line monitoring of power plant boilers. The main research work is as follows: (1) the feasibility of applying ZigBee technology to the system is analyzed, and the topology of wireless sensor network is determined. On this basis, the overall architecture design and the hardware and software design of the core parts are carried out. The hardware module circuit mainly includes sensor module, router module and coordinator module, and completes the data processing circuit and antenna circuit. Sensor related circuit peripheral circuit and power module circuit design, software design is responsible for the completion of sensor node program design, router node program design, The program design of the coordinator node and the software design of the monitoring center are used to analyze and mine the gas leakage data, and the steps of evaluating the leakage state of the boiler in power plant are given, which are equal weight grey target theory and entropy weight grey target theory. On the basis of this, the theory of AHP weight grey target is put forward to divide the assessment level of boiler gas leakage status in power plant, which effectively solves the problem of boiler leakage status identification without standard fault model. This paper provides a new way for boiler leakage state evaluation. 3) using the grey GM1 / 1) model to predict the gas leakage concentration data in the next time period. Finally, the relative error between the predicted value and the actual value is less than 8.5%, and the average relative error is controlled within 3.5%. The application research shows that the system has high stability in testing, and the introduction of grey system theory will provide a powerful theoretical support for the assessment of the leakage state and the prediction of gas leakage of the boiler in power plant, as well as the guarantee for the safe, stable and efficient operation of the boiler in the power plant.
【學位授予單位】：東北電力大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TN92;TP274;TM621.2

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