【摘要】：開發(fā)利用天然氣這一清潔能源,實施“西氣東輸”、“緬氣工程”、“川氣東送”、“陜氣進京”等一系列重大輸氣工程,是實現(xiàn)我國能源結(jié)構(gòu)調(diào)整、發(fā)展低碳經(jīng)濟的重大戰(zhàn)略決策,這給燃氣輸配系統(tǒng)的建設(shè)與發(fā)展帶來了新的機遇和挑戰(zhàn)。作為燃氣配送過程中的關(guān)鍵環(huán)節(jié),燃氣調(diào)壓器的安全性和高效性越來越受到人們的重視�，F(xiàn)有的燃氣調(diào)壓器通常采用傳統(tǒng)的直接作用式或間接作用式的機械調(diào)壓模式,這種機械調(diào)壓方式調(diào)壓精度低、穩(wěn)定性差。由此,會導(dǎo)致燃氣熱值下降,造成能源的極大浪費;同時,產(chǎn)生大量一氧化碳,造成環(huán)境污染,甚至可能誘發(fā)供氣安全等問題。因此,提高燃氣調(diào)壓器的調(diào)壓性能,已成為燃氣調(diào)壓技術(shù)領(lǐng)域的前沿課題。本文在深入研究現(xiàn)有調(diào)壓技術(shù)和控制理論的基礎(chǔ)上,以需求量最大的低壓燃氣調(diào)壓器為研究對象,提出并設(shè)計了一種新型的電動調(diào)壓模式。探索了電動燃氣調(diào)壓測控問題的新理論和新方法,提出一種基于PID神經(jīng)網(wǎng)絡(luò)的燃氣調(diào)壓測控方案,并采用FPGA實現(xiàn)了PID神經(jīng)網(wǎng)絡(luò)的燃氣調(diào)壓實時測控。本文的研究工作,有望提升燃氣調(diào)壓器的技術(shù)水平,以提高燃氣調(diào)壓的實時性、準確性和可靠性,為燃氣調(diào)壓器的工程設(shè)計提供科學(xué)依據(jù)。論文的主要工作包括:研究了現(xiàn)有的燃氣調(diào)壓技術(shù),建立了電動燃氣調(diào)壓的智能化測控方案;研究了工業(yè)中常用的PID控制技術(shù);針對現(xiàn)有控制算法在電動燃氣調(diào)壓測控的具體應(yīng)用問題,研究了人工神經(jīng)網(wǎng)絡(luò)算法,將人工神經(jīng)網(wǎng)絡(luò)與PID控制規(guī)則相融合,建立了基于PID神經(jīng)網(wǎng)絡(luò)的燃氣調(diào)壓控制算法;并用MATLAB對傳統(tǒng)PID控制算法和PID神經(jīng)網(wǎng)絡(luò)算法進行仿真對比,結(jié)果表明PID神經(jīng)網(wǎng)絡(luò)比PID控制具有更加優(yōu)越的性能;同時,用FPGA硬件平臺進行了算法實現(xiàn);最后以燃氣調(diào)壓器的氣壓控制系統(tǒng)為研究基礎(chǔ),對整個控制模塊進行空載時序仿真和加入燃氣調(diào)壓器系統(tǒng)模型仿真,仿真結(jié)果表明:PID神經(jīng)網(wǎng)絡(luò)氣壓控制模塊具有很高的控制精度和實時性,適用于解決大滯后、非線性調(diào)壓系統(tǒng)的智能控制問題。最后對本課題所做的研究進行了總結(jié),并對課題下一步的工作進行了展望。
[Abstract]:The development and utilization of natural gas as a clean energy source and the implementation of a series of major gas transmission projects, such as "West to East Gas Transmission", "Myanmar Gas Project", "Sichuan Gas to the East", and "Shaanxi Gas to Beijing", are a series of major gas transmission projects to realize the adjustment of China's energy structure. The important strategic decision of developing low-carbon economy brings new opportunities and challenges to the construction and development of gas transmission and distribution system. As a key link in gas distribution process, people pay more and more attention to the safety and efficiency of gas regulator. The traditional mechanical regulating mode of direct action or indirect action is usually used in the existing gas regulator, which has low precision and poor stability. As a result, the gas calorific value will decrease, resulting in a great waste of energy, at the same time, a large amount of carbon monoxide will be produced, resulting in environmental pollution, and even may lead to the safety of gas supply and so on. Therefore, improving the pressure regulation performance of gas regulator has become a frontier topic in the field of gas pressure regulation technology. On the basis of deep research on the existing voltage regulation technology and control theory, a new type of electric voltage regulating mode is proposed and designed in this paper, taking the low-pressure gas regulator with the greatest demand as the research object. In this paper, the new theory and method of electric gas pressure regulation and measurement and control are explored, and a new method of gas pressure regulation measurement and control based on PID neural network is put forward, and the real time measurement and control of gas pressure regulation based on PID neural network is realized by FPGA. The research work in this paper is expected to improve the technical level of gas regulator, in order to improve the real-time, accuracy and reliability of gas pressure regulation, and provide scientific basis for the engineering design of gas regulator. The main work of this paper is as follows: the existing gas pressure regulation technology has been studied, the intelligent measurement and control scheme of electric gas pressure regulation has been established, the PID control technology commonly used in industry has been studied. Aiming at the specific application of the existing control algorithms in the electric gas pressure regulation and measurement and control, the artificial neural network algorithm is studied, and the artificial neural network and PID control rules are combined to establish the gas pressure regulation control algorithm based on the PID neural network. The traditional PID control algorithm and PID neural network algorithm are simulated and compared with MATLAB. The results show that PID neural network has better performance than PID control, and the algorithm is implemented on FPGA hardware platform. Finally, based on the air pressure control system of the gas regulator, the simulation of the whole control module is carried out on the no-load timing simulation and the model simulation of the gas regulator system. The simulation results show that the PID neural network air pressure control module has high control precision and real-time performance, and it is suitable for solving the intelligent control problem of large lag and nonlinear voltage regulating system. Finally, the research of this topic is summarized, and the future work of the project is prospected.
【學(xué)位授予單位】：重慶大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TE97;TP273

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