A fast method of on-line coal identification in a drop-tube furnace

It has been proven that detecting the type of coal burning in the boiler is very important to the thermal power plants. But the identification of the coals online is hard, especially for the blended coals. In this paper, three flame information including average, standard deviation and oscillation frequency are extracted by a flame detector, and using the information extracted composes the flame feature matrixes. By calculating the correlation coefficient of the matrixes the coals can be identified well. For the method does not use complex calculation, it can be used to identify coals fast online. The experimentation has been done on the drop-tube furnace, 27 kinds of coals including 7 single coals and 20 blended coals are tested, and the result shows the method works well for the identification of the coals.