Abstract

Coal-fired power plant requires huge storage of coal. During the storage of coal, heat is accumulated inside the stock piles and eventually results in the self-combustion or coal fire, which is a very serious problem in the fuel management and environmental aspect of the power plant facilities. To detect and forecast the coal fire, various methods had been suggested but there are no proven early warning technology until today. Since the resistivity of the coal is strongly affected by temperature, we suggested the ERT (Electrical Resistivity Tomography) monitoring technology to identify the heat accumulation inside the coal stock pile, which can eventually provide an early warning method of coal fire in the power plant facilities. To prove the technology, we prepared a small scale coal stock pile and electrodes were placed on the bottom of the stock pile. In the inside of the coal pile, temperature was continuously increased by using heating tools and ERT monitoring data were acquired for a few days until real coal fire take place on site. The whole ERT monitoring data were processed and we tried the 4D inversion to obtain changes of 3D resistivity distribution with temperature changes. In the 4D inversion results, we could identify the systematic change of resistivity values due to the heating process. Although resistivity is increased in the very early heating stage, increased resistivity is evident with the increase of coal temperature until self-combustion of coal. Therefore, we could prove that 4D ERT monitoring technology is a very promising method to detect and forecast the coal fire in the power plant facility.

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