本文選題：回轉(zhuǎn)窯 + K-means�。� 參考：《北方工業(yè)大學(xué)》2017年碩士論文

【摘要】：鋁電解行業(yè)的發(fā)展與中國(guó)經(jīng)濟(jì)的健康發(fā)展息息相關(guān),本論文通過(guò)研究鋁電解生產(chǎn)過(guò)程中各個(gè)階段的工藝流程,旨在提高生產(chǎn)效率、減少資源浪費(fèi)、促進(jìn)安全生產(chǎn)。在鋁電解行業(yè)中,回轉(zhuǎn)窯是對(duì)石油焦進(jìn)行一系列復(fù)雜處理的大型環(huán)狀設(shè)備。通過(guò)研究回轉(zhuǎn)窯煅燒過(guò)程的工藝參數(shù),運(yùn)用數(shù)據(jù)挖掘理論,分析工藝參數(shù)對(duì)煅后焦質(zhì)量參數(shù)的影響,為科學(xué)認(rèn)識(shí)回轉(zhuǎn)窯工藝參數(shù)配置提供幫助。論文研究了鋁電解回轉(zhuǎn)窯煅燒工藝的理論知識(shí)及相關(guān)技術(shù),包括回轉(zhuǎn)窯煅燒工藝流程、回轉(zhuǎn)窯質(zhì)量參數(shù)評(píng)定標(biāo)準(zhǔn),學(xué)習(xí)軟件工程相關(guān)理論,學(xué)習(xí)數(shù)據(jù)挖掘相關(guān)知識(shí),研究課題需要的相關(guān)算法,包括K-means聚類算法、主成分分析法、BP神經(jīng)網(wǎng)絡(luò)算法、粒子群優(yōu)化算法等現(xiàn)代智能領(lǐng)域相關(guān)算法。具體研究?jī)?nèi)容包括:首先,本文研究回轉(zhuǎn)窯煅燒工藝的理論知識(shí)及相關(guān)技術(shù),對(duì)回轉(zhuǎn)窯質(zhì)量參數(shù)進(jìn)行分析,選用煅后焦的粉末電阻率和真密度作為分析對(duì)象,研究數(shù)據(jù)挖掘相關(guān)理論,運(yùn)用K-means聚類分析算法對(duì)回轉(zhuǎn)窯煅燒質(zhì)量參數(shù)進(jìn)行聚類分析,根據(jù)質(zhì)量參數(shù)數(shù)據(jù)與工藝參數(shù)數(shù)據(jù)時(shí)間對(duì)應(yīng)的特點(diǎn),將K-means算法分析后質(zhì)量參數(shù)的分類與工藝參數(shù)的分類對(duì)應(yīng),采用主成分分析法對(duì)工藝參數(shù)訓(xùn)練樣本和測(cè)試樣本降維。其次,本文針對(duì)粒子群算法容易陷入局部極值的問(wèn)題,提出基于鄰代競(jìng)爭(zhēng)的雜交粒子群優(yōu)化算法,通過(guò)融合BP神經(jīng)網(wǎng)絡(luò)挖掘算法,演化成DCHPSO-BP算法,改善收斂效率低和容易陷進(jìn)個(gè)體極值的缺陷,然后對(duì)降維后的工藝參數(shù)樣本進(jìn)行訓(xùn)練學(xué)習(xí),預(yù)測(cè)回轉(zhuǎn)窯工藝參數(shù)對(duì)質(zhì)量參數(shù)的影響,構(gòu)建回轉(zhuǎn)窯配置參數(shù)預(yù)測(cè)模型。最后,運(yùn)用軟件工程的設(shè)計(jì)思想,采用SSH集成架構(gòu),構(gòu)建完整的、輕量級(jí)的J2EE軟件開(kāi)發(fā)模型,設(shè)計(jì)并實(shí)現(xiàn)了回轉(zhuǎn)窯煅后焦質(zhì)量分析系統(tǒng)。系統(tǒng)設(shè)計(jì)的目的是通過(guò)配置工藝參數(shù),使用數(shù)據(jù)挖掘方法預(yù)測(cè)出該工藝參數(shù)配置會(huì)生產(chǎn)出何種類型的煅后焦,并且為企業(yè)生產(chǎn)決策提供幫助。
[Abstract]:The development of aluminum electrolysis industry is closely related to the healthy development of Chinese economy. This paper aims to improve the production efficiency, reduce the waste of resources and promote safe production by studying the technological process of each stage of aluminum electrolysis production.In aluminum electrolysis industry, rotary kiln is a series of complex treatment of petroleum coke ring equipment.By studying the process parameters of rotary kiln calcination process and using data mining theory, the influence of process parameters on calcined coke quality parameters is analyzed, which provides help for scientific understanding of technological parameters configuration of rotary kiln.In this paper, the theoretical knowledge and related technology of aluminum electrolysis rotary kiln calcination process are studied, including the process flow of rotary kiln calcination, the evaluation standard of rotary kiln quality parameters, the relevant theory of software engineering, and the relevant knowledge of data mining.The related algorithms needed in this paper include K-means clustering algorithm, principal component analysis (PCA) algorithm, BP neural network algorithm, particle swarm optimization (PSO) algorithm and so on.The specific research contents include: firstly, this paper studies the theoretical knowledge and related technology of rotary kiln calcination process, analyzes the quality parameters of rotary kiln, and selects the powder resistivity and true density of calcined coke as the analysis object.The related theory of data mining is studied, and the K-means clustering analysis algorithm is used to analyze the calcination quality parameters of rotary kiln. According to the characteristics of the time correspondence between the quality parameters data and the process parameters data,The classification of quality parameters after analysis by K-means algorithm corresponds to the classification of process parameters, and the dimension reduction of process parameters training samples and test samples is adopted by principal component analysis.Secondly, aiming at the problem that particle swarm optimization is easy to fall into local extremum, a hybrid particle swarm optimization algorithm based on neighbor competition is proposed in this paper. By combining BP neural network mining algorithm, the hybrid particle swarm optimization algorithm evolves into DCHPSO-BP algorithm.The defects of low convergence efficiency and easy trapping into individual extremum are improved, then the sample of process parameters after dimension reduction is trained and studied, the influence of process parameters on quality parameters of rotary kiln is predicted, and the prediction model of configuration parameters of rotary kiln is constructed.Finally, using the design idea of software engineering and SSH integrated framework, a complete and lightweight J2EE software development model is constructed, and the quality analysis system of calcined coke in rotary kiln is designed and implemented.The purpose of the system design is to use the data mining method to predict what type of calcined coke will be produced by configuring the process parameters and to provide help for the production decision of the enterprise.
【學(xué)位授予單位】：北方工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TF351;TP18

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