The Thermal Damage Investigation And Wind Temperature Prediction Research Of Panji No.3Colliery

Along with the deepening of coal mining depth, thermal damage become one of the problems of mine. Thermal damage not only increase the cost of coal mining, but also affect the safety of the coal mine production. Investigating the cause of thermal damage is the precondition to thermal damage governance, and predicting of underground wind temperature is the key to the thermal damage cooling design.This paper takes Panji No.3colliery as an example and test its’thermal parameters.using the formula, can calculate the proportion of heat source. According to the calculation results show that geotherm is the main factor of high temperature in downhole.In this paper, combining with the data of geothermal drilling and adopting the method of comprehensive analysis and regression analysis theory research geothermal distribution.The results show that shows that the average geothermal gradient of Panji No.3colliery is3.2℃/hm,belong to the geothermal anomaly area,and the level of-650m has between the fist heat harm scope and the second heat harm scope. Therefore, thermal damage problem of Panji No.3colliery is serious. The anomaly characteristics of the geotemperature is associated with a variety of geologic factors, Such as fold structure, the groundwater migration, rock lithology and magmatic activity. When analysed all kinds of mining geological data, we can be found that fold structure is the main factor resulting in abnormal geothermal.The thermal damage of Panji No.3colliery will result in a high temperature to underground wind, it need to take measures to cool. But design of the cooling need to evaluate underground wind temperature, otherwise it will lead to high cost or can not meet the cooling demand. So, temperature prediction of underground wind is the key to the cooling design. At present, wind temperature prediction model is mostly mathematics model, mathematical model can’t be promoted because its calculating formula is complex, some parameters of the formula is not easy to get. This article would improve the algorithm of Back Propagation (BP) neural network, and then use it to establish the model of wind temperature. The model in underworkings of Panji No.3colliery, such as the bottom of wellbore and11163driving face, achieve good prediction effect because of controlling temperature difference in1℃. So, the model predicted results have practical reference significance to the design of the cooling in Panji No.3colliery. In this paper, Based on the BP neural network, using the matlab language create a GUI interface of wind temperature prediction. The GUI interface has intelligent prediction function which Make the BP neural network to predict more simple.