Intelligent Control Method Of Coal Jigging Process

Jig is utilized widely in coal preparation plant as a universal, efficient and reliable coal preparation equipment. About 60 percent of raw coal is cleaned by jigging process in coal preparation plant. Jigging plays an important role in coal cleaning in our country.But the automation of jigs falls behind in china. In the automatic discharge system of jigging, the expectation value of bed depth depends on the manual work, and the simple logical control or conventional PID algorithm used in discharging can not satisfies the bed stabilizing. Although the digital air valve is adopted in jigs, the adjustment of air-water rule depends on the experiences of jig operators but automatic system. The parameters can not be adjusted stably and accurately due to the excessive human factors. The satisfying stratification according to density distribution can not be obtained, and the serious misplacing of different density material causes large number of cleaning coal lost or contaminated, which affects the efficiency and benefits of coal cleaning seriously.Multi-variable coupling each other, time-variant, heavy nonlinear characteristic are contained in jigging process. The precise mathematical model between product quality or separation efficiency and operational parameters can not be built because the process mechanism description is too complex and a large of uncertain factors exist. The effective control can not be achieved by conventional control theory and methods. Recently, artificial intelligent technology, such as expert system, fuzzy control and neural network, is introduced to complex process control, which provides an effective method of the jigging automation.This article studies the strategy and realized method of jigging process automation with intelligent control theory.The main influencing factors of jigging separation are analyzed deeply. The analysis shows that the distribution characteristic is closely relative toproduct quality. The misplaced material content in bed can be reflected by the standard deviation of normal distribution. The author puts forward that the target of jigging process control should be the optimum stratification state and the bed stratification state is affected by pulsing water characteristic, mobility of the jig bed and discharging process.The bed stratification state is a key factor in jigging process control. Y radial density detecting principle and technology is studied in the article, y radial sensor and subsequent circuit is developed. The key problems, such as the reliability of counting and antinoise are resolved, and this detector is applied in practice. Y radial source is Cs . Experiment shows that the Y radial density detector can measure the coal density in different bed depth precisely. Bed status can be reflected by combining density information with other state information.In jigging process, quantitative information and uncertain information (fuzzy information) appears at the same time and multi-factors associate each other. Some key factors cannot be described by mathematic model. The article studies the status identification based on fuzzy reasoning, and puts forward that bed mobility is expressed by density difference between compact period and mobility period, also the fuzzy judgment method based on density mean value, standard deviation, raw coal ash content and bed depth information. In order to study the relationship of all kinds of parameters, data acquisition and recording system is designed. Operational parameters, such as density, bed depth, raw coal ash content, feed velocity, air valve etc, are recorded for a long time. Simultaneously, the timing artificial float and sink test is carried out. The high identification precision of bed stratification status is acquired through the analysis of recording data on site using fuzzy judgment method.By large numbers of experiments, the adjustment relationship between air valve operational rule and pulsing water characteristic, the pulsing water characteristic and mobility of bed, also the mobility of be...