Experimental Research Of Temperature Monitoring And Prediction Of Spontaneous Ignition Of Coal Silo

Coal storage silos of power plant are widely applied due to their protecting environment,uniform feeding and flexible dispatch.However,stored coal may give out heat due to the long-term storage in a limited closed space,which results in oxidation reaction of coal and easily causes the temperature increment even spontaneous combustion of it.Therefore,the effective real-time monitoring of temperature of stored coal and the prediction of high-temperature heat source points are the premise to solve the problem of spontaneous combustion of stored coal.Aiming at the phenomenon that stored coal is prone to have spontaneous combustion in power plants,the test platforms of coal storage silo,whose diameters are respectively 1.5 m and 0.52 m,are designed and built.Temperature sensor is used to monitor the temperature variations of stored coal and silo wall.The temperature rise rate of heat source is varied by changing the position in the silo and heating power of heat source.Each test platform is tested several times,the results of the respective test conditions are compared and analyzed,and the temperature variation rule of every zone of stored cola is got in the heating process of heat source.The results of two test platforms with different diameters are compared and analyzed,which can get the common characteristics of the effect of high-temperature heat source on the temperature field of coal storage silo under different silo diameters.It uses ANSYS to erect the silo model,sets parameters and conducts calculation.The calculation data are applied by Back-Propagation(BP)neural network algorithm to train and predict the position of high-temperature heat source point and temperature data in the silo model,which shows that the result is reliable.Then BP neural network algorithm is used to train and predict the data obtained from the experiment of silo with a diameter of 1.5 m,which also shows that the result is reliable.Hence,it is verified that BP neural network algorithm can be applied to the prediction of the position and temperature of high-temperature heat source in the heating process of stored coal.Based on the test,the prediction of spontaneous combustion points of BP neural network,and VC6.0 software,the smart safety monitoring system of coal storage silo is developed to conduct the real-time monitoring of the temperature variation of each test point in the silo.The monitoring system firstly stores the data into the MySQL database,which are collected by the sensor and acquisition board,and then displays the stored data in real time through the developed display interface.The system realizes the function of real-time monitoring of the temperature in coal storage silo.