Image Processing Based Experimental Study On The Growth Characteristics Of Ash

For a long period of time, Chinese energy consumption will continue to be coal-based. Chinese coal consumption for the coal-fired power generation is in the relatively high proportion. According to China’s energy policy, the coal of coal-fired power plant is generally of low rank coal, and the low-rank coal can cause serious boiler furnace slagging problem. The slagging problem can make a serious impact to the safe operation of the coal-fired power plants, therefore it is necessary to study on the growth process of the ash on the furnace of heating surface.In order to study the growth characteristics of the ash, the Ningxia coal and PRB coal were chose as the test coal. The one-dimensional test furnace and the deposition probe were used to analog condition the growth of ash in the boiler. The CCD camera system were used to get the coal slagging process image information, the ash thickness can be extracted by the image progress, and ash distribution of the ash can extract from the image by the two-color method.By processing and analyzing the all information, the result show that Ningxia Coal is more slaaging than the PRB coal; the chemical composition of the ash have a certain influence. The growth process of ash can be clearly divided into different stages and different stages of the slagging have different influence on the heat flux. The change of the slag’s thickness is a process that from a rapid growth state to a steady state; ash surface temperature distribution in different time showed that the temperature gradually decreased from outside to inside, low-temperature region is enlarged with the growth of ash, ash temperature distribution show a strong hierarchy. By analyzing Ningxia Coal and PRB coal slagging image, high heat resistance which can be found in the initial layer of ash on the growth of ash is extremely important for the slagging. By comparing the thermocouple temperature of furnace wall and ash temperature distribution information it show that the temperature field extracted from the image can accurately reflect the ash surface temperature information.