本文選題：信息化平臺 + 重介質選煤�。� 參考：《曲阜師范大學》2017年碩士論文

【摘要】：煤炭是一種不可再生能源,隨著生產生活的消耗,其儲量迅速下降。但是其作為國家基礎性能源的地位沒有變,國家眾多產業(yè)還是以其為基礎。但是目前就國內情況來說,我國煤炭利用率不高,選煤廠信息化水平較低,選煤精度較差。尤其是在重介質選煤密度控制問題上,采用常規(guī)PID控制,易出現(xiàn)大滯后、非線性,現(xiàn)有的選煤工藝已經不能滿足市場的要求,并且整個生產過程中信息化存在“孤島效應”。本文旨在實現(xiàn)選煤過程的信息化控制,設計重介質選煤智能技術控制系統(tǒng),來提高選煤的產量和精度。本文以選煤廠為工業(yè)背景,介紹了智能控制技術在選煤信息化系統(tǒng)中的實際應用,敘述了選煤工藝流程,針對選煤廠的信息滯后問題,設計了以工業(yè)以太網(wǎng)為核心的綜合信息化平臺。該平臺將儲運集控中心、原煤集控中心、中心調度室、重介水洗車間、儲運配電室和重介選矸等分別安裝以太網(wǎng)交換機并鋪設光纜,形成一副巨大的工業(yè)環(huán)網(wǎng),由調度中心統(tǒng)一管理調控。實現(xiàn)關鍵工藝節(jié)點參數(shù)在線檢測、信息化數(shù)據(jù)傳輸,選煤過程控制自動化以及生產數(shù)據(jù)綜合到綜合信息化平臺上,實現(xiàn)數(shù)據(jù)的整合。從而為管理人員提供重要數(shù)據(jù)參考,來對現(xiàn)場設備的運行狀態(tài)自動檢測,實現(xiàn)選煤系統(tǒng)信息化控制。重介質旋流器中的懸浮液密度是影響選煤精度和質量的關鍵因素,不同密度波動下能生成含雜率不同的精煤,需要控制密度在恒定狀態(tài)下才能分離出最優(yōu)的產品。為了實現(xiàn)重介選煤過程的數(shù)據(jù)自動調控和密度恒定控制目標,本文重點研究了重介質密度控制系統(tǒng),利用計算法建立了數(shù)學模型,近似為二階純遲延函數(shù)。設計了重介質密度控制器,該控制器基于PSO和BP神經網(wǎng)絡算法,結合PSO算法的選優(yōu)能力和BP神經網(wǎng)絡的自學習能力,將控制重介質旋流器懸浮液密度的PID參數(shù)進行了優(yōu)化,實現(xiàn)了控制參數(shù)的實時在線整定。通過仿真結果顯示,該算法響應速度快、穩(wěn)態(tài)誤差小、魯棒性和可調性強,能很好的解決重介選煤過程中出現(xiàn)的大滯后、非線性問題。其算法實現(xiàn)過程主要是通過OPC技術實現(xiàn)對工藝過程的數(shù)據(jù)采集,然后借助MATLAB軟件工具實現(xiàn)PSO_BPPID優(yōu)化算法,最終把運算后的數(shù)據(jù)送給監(jiān)測平臺進而傳送給現(xiàn)場控制裝置。此過程中監(jiān)測平臺與控制裝置借助于實時以太網(wǎng)技術實現(xiàn)簡單的數(shù)據(jù)傳輸。通過對選煤過程的優(yōu)化設計,大大提高了選煤過程中的可靠性和穩(wěn)定性,設備故障頻率明顯降低,控制精度和生產效率明顯提高,同時以太網(wǎng)技術的引入也大大提高了煤礦生產過程的信息化建設。
[Abstract]:Coal is a kind of non-renewable energy, with the consumption of production and life, its reserves decline rapidly. But its status as the national basic energy has not changed, the country's many industries are based on it. But at present, the utilization ratio of coal is not high, the information level of coal preparation plant is low, and the precision of coal preparation is poor. Especially in the density control of heavy medium coal preparation, the conventional PID control is easy to appear large lag, nonlinear, the existing coal preparation technology can not meet the requirements of the market, and the entire production process information exists in the "island effect". The purpose of this paper is to realize the information control of coal preparation process and to design the intelligent control system of heavy medium coal preparation to improve the production and precision of coal preparation. Taking the coal preparation plant as the industrial background, this paper introduces the practical application of intelligent control technology in the coal preparation information system, and describes the coal preparation process, aiming at the information lag problem of the coal preparation plant. A comprehensive information platform based on industrial Ethernet is designed. The platform will install Ethernet switch and lay optical cable in storage and transportation centralized control center, raw coal centralized control center, central dispatching room, heavy medium washing workshop, storage and distribution room and heavy medium gangue respectively, forming a huge industrial ring network. By the dispatch center unified management control. The key process node parameters on-line detection, information data transmission, coal preparation process control automation and production data integration on the integrated information platform are realized, and the data integration is realized. So it can provide important data reference for managers to automatically detect the running state of field equipment and realize the information control of coal preparation system. The density of suspensions in heavy medium hydrocyclone is the key factor to affect the precision and quality of coal preparation. Under different density fluctuation, the fine coal with different impurity content can be produced, and the optimal product can be separated only when the density is controlled in a constant state. In order to realize automatic data control and constant density control in heavy medium coal preparation process, the density control system of heavy medium is studied in this paper, and the mathematical model is established by using the calculation method, which is approximate to the second order pure delay function. A dense medium density controller is designed. Based on the algorithm of PSO and BP neural network, the parameters of PID which control the density of suspensions of heavy medium cyclone are optimized by combining the optimization ability of PSO algorithm and the self-learning ability of BP neural network. Real-time online tuning of control parameters is realized. The simulation results show that the algorithm has the advantages of high response speed, small steady-state error, strong robustness and tunability, and can solve the problem of large lag and nonlinearity in the process of heavy coal preparation. The realization process of the algorithm is mainly to realize the data acquisition of the process process through OPC technology, and then realize the PSO_BPPID optimization algorithm by means of the MATLAB software tool. Finally, the data after calculation is sent to the monitoring platform and then transferred to the field control device. In this process, the monitoring platform and control device realize simple data transmission by means of real-time Ethernet technology. Through the optimization design of coal preparation process, the reliability and stability of coal preparation process are greatly improved, the frequency of equipment fault is obviously reduced, and the control precision and production efficiency are obviously improved. At the same time, the introduction of Ethernet technology has greatly improved the information construction of coal mine production process.
【學位授予單位】：曲阜師范大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TD94;TP273

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