数据挖掘方法在炭黑反应炉生产分析中的应用
文献类型：学位论文
| 作者 | 张世伟 |
| 学位类别 | 工学硕士 |
| 答辩日期 | 2013-05-24 |
| 授予单位 | 中国科学院大学 |
| 授予地点 | 中国科学院自动化研究所 |
| 导师 | 曾隽芳 |
| 关键词 | 炭黑 数据仓库 数据挖掘 工业数据分析 Carbon Black Data warehouse Data Ming Industrial Data Analysis |
| 其他题名 | Application of Data Mining On the Analysis of Carbon Black Furnace Production |
| 学位专业 | 计算机应用技术 |
| 中文摘要 | 炭黑是许多烃类物质经过不完全燃烧或裂解生成的超细的烟炱，被广泛应用作橡胶，涂料和油墨等工业等的基本原料，也是橡胶制品的重要补强材料和填充材料。全球范围内对炭黑的需求量以每年平均3%左右的增长率递增。传统炭黑生产方式不仅能耗高，而且环境污染严重。随着全球气候问题和环境污染问题的加剧，低碳已经成为全球社会经济发展的主要趋势，炭黑行业也加大力度实施节能减排和发展循环经济。目前干法造粒炭黑在我国已经被淘汰，而节能减排效果相对较好的湿法造粒炭黑成为主要的炭黑生产方法。 近年来，炭黑行业已经取得了长足的发展，但是仍然存在原料不足，环境污染等问题，不仅如此，炭黑生产反应炉结构复杂，生产过程中工艺参数众多因此工艺条件仍有很大的优化空间。本文针对炭黑生产过程中存在的工艺参数调节困难这一问题，研究将数据挖掘技术用于分析炭黑生产反应炉所积累的过程数据和炭黑产品化验数据，分析生产炭黑产品的工艺操作条件与炭黑产品之间的关系以及不同的生产模式，主要进行三个方面的工作。首先，构建了炭黑生产数据分析系统，该系统能够对采集到的过程数据进行存储，按照分析的要求存储在数据仓库中。为操作人员提供关于当前以及历史生产过程中工艺参数的查询和分析任务。其次，构建炭黑生产历史数据的数据仓库，炭黑生产过程中所产生的数据是过程数据，本身各个参数之间没有联系，而要进行分析时需要将大量的数据进行预处理和整合，然后存储在数据仓库中，为工艺分析以及生产状况分析打下了基础。第三，结合数据挖掘算法对工艺进行分析，得出了在原料未不生变化的情况下，生产同一种类型的炭黑产品如何调节工艺参数，以及对相同原料条件下生产不同类型炭黑产品如何调节工艺参数，并给出了许多生产条件下的参考值。不仅如此，还为以后系统的扩展，如炭黑的产率，生产状况，耗能等情况的分析打下了基础。 通过以上工作，探索了数据挖掘技术在分析炭黑反应炉生产分析中的应用，为构建可行的炭黑企业数据分析和优化系统打下了一定的基础。 |
| 英文摘要 | Carbon Black is a kind of superfine soot coming from the incomplete combustion of hydrocarbons; it is widely used as the basic materials in the produce of rubber, paint and ink industry; it is also the important reinforcing materials and packing materials of rubber products. The total amount of carbon black demand in the global grows 3% every year. The traditional way of producing carbon black is not only high energy consumption, but also serious environmental polluting. With the global climate and environment becoming worse and worse, in recent years, low carbon consumption has become the main trend of the development of modern society. Carbon black industry also needs to pay more attention in improving the way of product production and developing recycling economic. In China, the old way has already been eliminated and the way of wet producing method has already take the majority of the whole industry, reaching to no less than 94%. Over so many years, the way of producing Carbon Black has already improved a lot, and the device of the Carbon Black Production is also becoming more and more advanced, however, problems still exist in Carbon Black industry. The first problem is the shortage of material in producing Carbon Black, ethylene, coal tar and natural gas are at a shortage state while all of them are the main material in the produce of Carbon Black. Another serious problem is environment pollution, especially the waste gas from the Carbon Black Furnace. Besides, the Because of the complexity of the process of Carbon Black and so many parameters , the quality of Carbon black product relys on the experience of the technician, sometimes, it may lead to problems. The quality of the product can’t be guaranteed. This paper delves into the problems existing in the process of producing Carbon Black. By combing the method of Data Mining and the historical data collected in producing Carbon Black and the quality parameters of the Carbon Black product, some major problems have been solved. The major work includes the following aspects: First, a data collection system was built. This system not only collects the process data, but also collects the production data. The collected data are stored in the database for querying and analysis in the future. Second, a data warehouse storing process data and production data was designed. The initial data can’t be directly used in the process of analysis. Data warehouse is used for storing huge amount of data. The dat... |
| 语种 | 中文 |
| 其他标识符 | 201028014628023 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/7676]  |
| 专题 | 毕业生_硕士学位论文 |
| 推荐引用方式 GB/T 7714 | 张世伟. 数据挖掘方法在炭黑反应炉生产分析中的应用[D]. 中国科学院自动化研究所. 中国科学院大学. 2013. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。