The Study Of Coal Calorific Capacity Based On Texture Feature

The coal calorific capacity is the important target of evaluate coal quality for good or bad,is the main parameter of calculation of standard coal consumption in thermal power plant,is the main parameter of thermal power plant calculate standard coal consumption,is also an important reference parameter of boiler operation,if can provide coal calorific capacity of enter the furnace coal,it has very important significant for guaranteed that the boiler working by safely and stably.Traditional method of measure coal calorific capacity operated troublesome and process duration is long,it unable to satisfy the instantaneity request,moreover pollution of environment,it's bad for staff's health. In order to overcome the above shortcomings,this paper propose a new method of survey the coal calorific capacity.This method can realize measure of coal calorific capacity according to the digital image processing technology and the artificial neural networks pattern recognition technology. This method produce on the basis of the different type coal has different texture characteristic value and it produces the calorific capacity is also different. First,building a sample storehouse,it includes each kind of coal and its corresponds calorific capacity. If want to test coal calorific capacity only testing coal texture image after pretreatment,extract the texture characteristic value,then take the texture characteristic value as an input vector to substitute netural network that it trains good and distinguish the type of testing coal,finally to search its corresponding the calorific capacity arrives in the sample storehouse.When realize the coal texture image classification and the recognition,this paper used in the artificial neutral BP network,distinguish finally the accuracy has achieved 100%.Through the final result,it indicate that present paper attempts the new method has certain feasibility,it has laid the rationale for the following research coal calorific capacity.