本文選題：煉鋼廠(chǎng) + 動(dòng)態(tài)運(yùn)行��； 參考：《北京科技大學(xué)》2016年博士論文

【摘要】：隨著“高效率、低成本潔凈鋼平臺(tái)集成技術(shù)”和鋼鐵生產(chǎn)過(guò)程“智能制造”的提出,煉鋼廠(chǎng)動(dòng)態(tài)運(yùn)行過(guò)程管控越來(lái)越受到重視,但對(duì)煉鋼廠(chǎng)動(dòng)態(tài)運(yùn)行過(guò)程基本參數(shù)(物流量、溫度和時(shí)間因子)的系統(tǒng)研究仍處于前期,特別是對(duì)基本參數(shù)控制精度的研究還是空白。本文將針對(duì)遷鋼第二煉鋼廠(chǎng)動(dòng)態(tài)運(yùn)行過(guò)程中若干工序基本參數(shù)進(jìn)行分析,分別對(duì)物流量、鋼水溫度和時(shí)間的管控以及精準(zhǔn)控制下的節(jié)能潛力四個(gè)方面進(jìn)行研究。本文分析了遷鋼第二煉鋼廠(chǎng)的轉(zhuǎn)爐工序、精煉工序、連鑄工序、鋼包周轉(zhuǎn)、傳擱過(guò)程的主要工藝參數(shù)和控制現(xiàn)狀,以及RH精煉、210t LF精煉和傳擱過(guò)程中鋼水溫降與物料消耗和時(shí)間的關(guān)系。由物流量控制現(xiàn)狀的解析得知：轉(zhuǎn)爐冶煉過(guò)程實(shí)現(xiàn)了少渣冶煉,氧氣消耗量和利用率相對(duì)穩(wěn)定,但噸鋼鐵損較大。針對(duì)該問(wèn)題,提出針對(duì)每一爐次具體的原料條件,動(dòng)態(tài)調(diào)整冶煉輔料加入量的策略,實(shí)例計(jì)算結(jié)果表明,噸鋼鐵損可以減少4kg/t鋼。分別對(duì)各工序節(jié)點(diǎn)鋼水溫度的預(yù)定和預(yù)報(bào)進(jìn)行了管控研究。前者是指在合理的溫度制度的基礎(chǔ)上,考慮連澆爐次、各工序及其傳擱過(guò)程時(shí)間、鋼包狀態(tài)等因素動(dòng)態(tài)調(diào)整各工序節(jié)點(diǎn)的控制溫度；后者是以上一工序節(jié)點(diǎn)的鋼水溫度為基礎(chǔ),預(yù)報(bào)下一工序節(jié)點(diǎn)的鋼水溫度,進(jìn)而連接實(shí)現(xiàn)全流程的鋼水溫度預(yù)報(bào)。分別結(jié)合RH和210t LF兩種精煉工藝的特點(diǎn),運(yùn)用改進(jìn)的案例推理方法對(duì)鋼水溫度預(yù)報(bào)進(jìn)行研究,該方法可以應(yīng)用于其他區(qū)段,進(jìn)而實(shí)現(xiàn)全流程的鋼水溫度預(yù)報(bào)。結(jié)合RH精煉已積累了大量生產(chǎn)數(shù)據(jù)的特點(diǎn),提出了案例庫(kù)拆分和優(yōu)化的措施以提高案例推理方法的預(yù)報(bào)精度和運(yùn)算速度,實(shí)際數(shù)據(jù)測(cè)試結(jié)果表明,基于拆分案例庫(kù)的案例推理方法的預(yù)報(bào)精度明顯高于單一案例庫(kù)的預(yù)報(bào)精度,基于優(yōu)化案例庫(kù)的案例推理方法運(yùn)算時(shí)間僅為優(yōu)化前的44%,運(yùn)算效率大幅提升。結(jié)合210t LF精煉的工藝參數(shù)關(guān)聯(lián)性復(fù)雜的特點(diǎn),提出利用貝葉斯網(wǎng)絡(luò)對(duì)生產(chǎn)數(shù)據(jù)可靠性進(jìn)行評(píng)估,并利用評(píng)估結(jié)果對(duì)案例推理方法進(jìn)行修正。測(cè)試結(jié)果表明,修正后的案例推理方法比一般案例推理方法和BP神經(jīng)網(wǎng)絡(luò)都有更高的預(yù)報(bào)精度。在煉鋼廠(chǎng)時(shí)間因素管控中,分別對(duì)確定合理連澆爐數(shù)、優(yōu)化不同澆次間關(guān)系和鋼包調(diào)度水平的評(píng)價(jià)方法進(jìn)行研究。在BOF-RH-CC工序產(chǎn)能不匹配的情況下,提出了基于傳擱能耗計(jì)算,進(jìn)而對(duì)比生產(chǎn)成本的方法確定合理連澆爐數(shù)。為了優(yōu)化不同澆次間關(guān)系,在非滿(mǎn)負(fù)荷生產(chǎn)條件下,提出以鋼包運(yùn)行穩(wěn)定性為目標(biāo),采用遺傳算法對(duì)已有生產(chǎn)計(jì)劃進(jìn)行優(yōu)化,對(duì)遷鋼二煉鋼2013年某日實(shí)際生產(chǎn)計(jì)劃優(yōu)化后的結(jié)果表明,該日周轉(zhuǎn)鋼包離線(xiàn)次數(shù)由5次減少到1次,必須投入鋼包個(gè)數(shù)由7個(gè)減少到5個(gè),可節(jié)約烘烤煤氣20400m3,避免轉(zhuǎn)爐對(duì)離線(xiàn)鋼包所需的鋼水溫度補(bǔ)償20℃。對(duì)鋼包調(diào)度水平的研究,提出基于待用時(shí)間解析的方法分別評(píng)價(jià)周轉(zhuǎn)鋼包和離線(xiàn)鋼包的運(yùn)行現(xiàn)狀,并擬合為鋼包利用率用以評(píng)價(jià)鋼包整體調(diào)度水平,通過(guò)對(duì)遷鋼二煉鋼鋼包調(diào)度進(jìn)行實(shí)例分析,結(jié)果表明鋼包利用率可以有效的反映實(shí)際鋼包調(diào)度水平。針對(duì)鋼水溫度和時(shí)間因素精準(zhǔn)控制下能潛力問(wèn)題,根據(jù)實(shí)際操作要求,通過(guò)解析生產(chǎn)計(jì)劃的制定和執(zhí)行過(guò)程,得到二者在現(xiàn)有控制精度下節(jié)能潛力的數(shù)學(xué)模型。結(jié)合遷鋼二煉鋼SPHC-W鋼種冶煉過(guò)程,將各階段鋼水溫度和時(shí)間生產(chǎn)數(shù)據(jù)統(tǒng)計(jì)的標(biāo)準(zhǔn)差表征為控制精度,對(duì)現(xiàn)有控制水平進(jìn)行實(shí)例研究,結(jié)果表明,當(dāng)各工序節(jié)點(diǎn)鋼水溫度的標(biāo)準(zhǔn)差減小1℃時(shí),計(jì)劃執(zhí)行預(yù)知溫度損失降低0.33℃,當(dāng)各工序時(shí)間標(biāo)準(zhǔn)差減小1 min時(shí),生產(chǎn)計(jì)劃預(yù)知溫度損失降低1.76℃C,計(jì)劃執(zhí)行預(yù)知溫度損失降低1.62℃,二者同時(shí)減小時(shí)表現(xiàn)出可疊加性。
[Abstract]:With the introduction of "high efficiency, low cost clean steel platform integration technology" and "intelligent manufacturing" of steel production process, the control and control of the dynamic operation process of the steelmaking plant has been paid more and more attention. However, the systematic research on the basic parameters of the dynamic process of the steelworks (logistics, temperature and time factors) is still in the early stage, especially for the basic parameters control. The research on the precision of the system is still blank. This paper will analyze the basic parameters of some processes during the dynamic operation of the second refinery, and study the four aspects of the flow, the temperature and time of the molten steel and the energy saving potential under the precision control. This paper analyzes the converter process and the refining process of the second refinery. The main process parameters and control status of the continuous casting process, ladle turnover and transmission process, as well as the relationship between temperature drop of steel water and material consumption and time during the process of RH refining, 210t LF refining and transmission, and the analysis of the current situation of flow control in the converter: the converter smelting process has realized less slag smelting, oxygen consumption and utilization are relatively stable, but tonn steel In view of this problem, the strategy of dynamic adjustment of the amount of smelting auxiliary material is put forward according to the specific raw material conditions of each furnace. The calculation results show that the steel loss of tons can be reduced by 4kg/t steel. The control and control of the temperature of the steel water in each process is studied. The former refers to the basis of the reasonable temperature system. The control temperature of each process node is dynamically adjusted by factors such as continuous casting, each process and its transmission time, ladle state and other factors. The latter is based on the temperature of the steel water of the above working procedure node, and the temperature of the steel water in the next process node is predicted, and then the temperature of the whole process is connected with the two kinds of RH and 210t LF respectively. The characteristics of refining process, using improved case reasoning method to study the temperature prediction of steel water, this method can be applied to other sections, and then realize the whole process of molten steel temperature prediction. Combined with the characteristics of RH refining has accumulated a large amount of production data, a case base separation and optimization measures are proposed to improve the preview of case reasoning method. The actual data test results show that the prediction accuracy of the CBR Based on the Split case base is obviously higher than that of the single case base. The time of the case based reasoning method based on the optimized case base is only 44% before optimization, and the operation efficiency is greatly improved. Combined with the process parameters Association of 210t LF refining. A Bayesian network is used to evaluate the reliability of production data, and the results of the evaluation are used to modify the case reasoning method. The test results show that the modified CBR has a higher pre reporting precision than the general case reasoning method and the BP neural network. In the time factor control of the steelworks, respectively The evaluation method of determining the number of reasonable pouring furnace, optimizing the relationship between different pouring times and the level of ladle scheduling is studied. In the case of the mismatch of the production capacity of the BOF-RH-CC process, a method is put forward to determine the number of reasonable pouring furnaces based on the calculation of the energy consumption and the comparison of the production cost. Under the condition, the existing production plan was optimized by genetic algorithm. The result of optimization of the existing production plan was made by genetic algorithm. The results showed that the off-line number of off line ladles was reduced from 5 times to 1 times in 2013, and the number of ladles must be reduced from 7 to 5, and the roasted gas 20400m could be saved by 20400m. 3, avoid the converter's temperature compensation for the water temperature required for the off-line ladle at 20. Study on the scheduling level of the ladle, and propose a method to evaluate the running status of the revolving ladle and the off-line ladle respectively based on the analysis of the waiting time, and fit the utilization rate of the ladle to evaluate the overall scheduling of the ladle, and to carry out an example of the transfer of steel ladle for the transfer of steel two. The results show that the ladle utilization rate can effectively reflect the actual ladle scheduling level. According to the precise control of the potential of the temperature and time of the steel, according to the actual operation requirements, the mathematical model of the energy saving potential of the two persons under the existing control precision is obtained by analyzing the process of making and executing the production plan. The model is combined with the moving steel two. The smelting process of steel SPHC-W steel in steelmaking is characterized by the standard deviation of the statistics of the temperature of the steel water and the time production data at various stages. The existing control level is studied by an example. The results show that when the standard deviation of the molten steel temperature of each process is reduced by 1 degrees C, the predicted temperature loss is reduced by 0.33 degrees C, and the standard deviation of each process time is reduced. When 1 min is small, the production plan foresee that the temperature loss will be reduced by 1.76 degrees C, the planned implementation of predicted temperature loss will be reduced by 1.62 degrees, and the two will be superimposed at the same time.

【學(xué)位授予單位】：北京科技大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類(lèi)號(hào)】：TF345

【參考文獻(xiàn)】

相關(guān)博士學(xué)位論文 前1條

1 王建軍;鋼鐵企業(yè)物質(zhì)流、能量流及其相互關(guān)系研究與應(yīng)用[D];東北大學(xué);2008年

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本文編號(hào)：1818154