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Research On Temperature Control Of Cement Rotary Kiln Based On Big Date Analysis

Posted on:2022-10-29Degree:MasterType:Thesis
Country:ChinaCandidate:Q Y LiFull Text:PDF
GTID:2491306347973829Subject:Control Science and Engineering
Abstract/Summary:PDF Full Text Request
The burning process of the material in the rotary kiln is the most critical process in cement production,and the control effect of the rotary kiln temperature directly affects the free calcium oxide content of the clinker,which in turn determines the quality of the cement clinker.However,due to the complicated burning conditions in domestic cement production,most of the cement companies in China are still in the manual control stage for the rotary kiln segment,which is subject to the knowledge workers’ experience and personal subjective factors,making it difficult to achieve the desired effect of rotary kiln temperature control;In addition,the cement clinker firing process involves many variables,a wide range of data sources and inconsistent time scales,resulting in a large amount of data from cement plants that are not fully utilized.Therefore,it is important to combine big data analysis technology and adopt effective methods to achieve reasonable temperature control of rotary kiln system for normal production of cement clinker and improvement of cement quality qualification rate.In response to the above problems,this subject takes a clinker production line with a daily production capacity of 5000 tons in a cement plant in Shandong Province as the research background,and realizes the scheme design of cement rotary kiln temperature control system and the development of control software by analyzing a large amount of industrial data and summarizing the excellent control experience of knowledge workers,and combining the case inference algorithm and fuzzy expert rules.The main research contents of this paper are as follows.(1)Multi-source data processing of cement rotary kiln burning process.Firstly,according to the cement clinker burning process,the initial set of variables that can characterize the burning conditions of rotary kiln is established by integrating the relevant firing temperature data from infrared thermal imager,online data from DCS(Distributed Control System)operating system and offline testing data from laboratory;Secondly,according to the characteristic attributes of the selected variables,the corresponding filtering methods are selected for data pre-processing,and the multi-source data at different time scales are matched;Finally,the real-time value characteristics and trend characteristics of the selected variables are extracted.(2)Big data analysis of cement rotary kiln firing process.The processed multi-source data are analyzed by the gray correlation method,and the initial set of variables selected in the previous section is further streamlined to determine the simplest set of variables that can characterize the firing conditions of the rotary kiln.(3)A study on the temperature control of cement rotary kiln.Firstly,the initial case library is established based on the above-determined simplest set of variables and the real-time magnitude and trend characteristics of the variables,and the initial case solution of cement rotary kiln temperature control is given by the method of case inference;Secondly,the fuzzy expert rule is used to modify the initial case solution that some elements in the initial case solution set do not match with the current firing conditions.(4)Design and development of temperature control software for cement rotary kiln.Based on the above research results,a cement rotary kiln temperature control system based on big data analysis is designed and developed,and the design and implementation of modules such as data fusion,data communication and storage,feature extraction and core control are also completed.Finally,the cement rotary kiln temperature control system was actually put into operation in a clinker production line with a daily production capacity of 5000 tons in a cement plant in Shandong.The field application shows that the research results of this paper reduce the labor intensity of knowledge workers,can realize the real-time monitoring of cement production process parameters and reasonable control of rotary kiln system temperature,and improve the quality of cement clinker products.
Keywords/Search Tags:rotary kiln temperature control, big data technology, grey correlation degree, case-based reasoning, fuzzy expert rule
PDF Full Text Request
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