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Application Of Data Fusion Technology In The Ball Mill Detecting Material Level

Posted on:2011-07-15Degree:MasterType:Thesis
Country:ChinaCandidate:D W ZhaoFull Text:PDF
GTID:2132330332470972Subject:Pattern Recognition and Intelligent Systems
Abstract/Summary:PDF Full Text Request
Ball Mill has large capacity, reliable operation, adapts to many kinds of coal, repairs easily and inexpensively. It has become the most equipment in the domestic coal-fired power plant milling system. The academic study and practical run both show that the ball mill pulverizing system runs closely with the material level. At present, we mainly uses pressure difference between export and import, grinding sound signal, power and other traditional methods to detect the material level in the actual production, but the ball mill is a multivariable, nonlinear, serious coupling and large delay object, it has a number of parameters, and the coupling between parameters is serious. Only gathering one of the parameters to reflect the material level can not get perfect results.Data fusion is a new information processing technology, it was used in the military sphere first.It is a process to combine the multisource information for target detection, association, state evaluation. Its theories and methods have become in the intelligent information processing and control.The paper first studied the running characteristics of ball mill, summarized the actuality of ball mill material level detection, understood the advantages and disadvantages of the present methods of material level detection, applied the data fusion to the ball mill material level detection through argumentation. The project collected the ball mill grinding sound signals, pressure difference between import and export, temperature difference between import and export, import negative pressure as fusion parameters, selected the BP neural network method, used its powerful information comprehensive capabilities, ability of knowledge generalization, and the fault-tolerance of structure as a fusion algorithm in the data layer, and completed the fusion simulation of BP neural network. From the simulation results we can see that using data fusion technology can achieve more accurate detection of ball mill material level, and make the ball mill to consistently run in the more efficient operating condition, improve the efficiency of ball mill, reduced the ball mill power consumption, in order to establish the foundation of the optimized control of ball mill.
Keywords/Search Tags:data fusion, BP neural network, ball mill, detection of material level
PDF Full Text Request
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