Study Of Source Discrimination Of Coalmine Water Inrush Based On EIM And FCE

Water disaster is regarded as one of the major disasters in the colliery,which directly threatens the safety of coalmine production and construction. As the water inrush happens, it is fundamental for the effective prevention and treatment of coalmine water disaster to discriminate the source of water-busting accurately and timely. Therefore, the algorithms of coalmine water-bursting source are very important in the process of comprehensive dealing with water disaster.Firstly, this paper analyzes the chemical characteristic of each aquifer in the minefields and then studies the regularity of distribution of the main ions in each aquifer; Secondly, this paper uses the extension identification method and the fuzzy comprehensive evaluation to establish the mathematical models of water source discrimination. After that, a new extension identification method is proposed to calculate the location value. At the same time, the fuzzy comprehensive evaluation is also improved by Huber-M estimators of the discrimination index in each aquifer instead of the standard values. Later, two enhanced water source discrimination models are established, respectively; Finally, this paper develops an decision-assistant system by C#language, to discriminate the coalmine water-bursting source and realize the intelligent management of water source discrimination.The main conclusions and results of this paper are as follows:The improved extension identification method improves the water source discrimination accuracy by solving a misjudgment problem, which the discrimination index data of the water samples being tested are not in the classical fields of other aquifers. Compared with the former results, the extension identification method increases the accuracy from47.3%to82.61%.The other method called improved fuzzy comprehensive evaluation enhances the reliability and accuracy of the discrimination model by using Huber-M estimator to decrease the influences of outliers or extrem value. Compared with the former results, the fuzzy comprehensive evaluation improves the accuracy of water source discrimination from70%to76.67%.Finally, the system with these two methods for coalmine water-inrush source discrimination achieves the dynamic management functions in adding data、deleting data、importing and exporting data, as well as the quick discrimination functions and so on.The research has significant and practical values for water controls in coalmines, and it provides the theoretical basis for the prevention and treatment of coalmine water work.