Study On The Subsidence Monitoring Of Main And Auxiliary Shaft Headframe Foundations Of WOLONG LAKE Coal Mine

In recent years, shafts in mines of Huaibei and Huainan, as well as Xuzhou, have been destroyed at different levels. According to monitoring data, the grounds of the mining regions and industry squares have suffered from obvious coalmining subsidence when shafts were destroyed. In order to ensure the safety production, the paper analyses the rule of ground subsidence, builds predictive model by the subsidence monitoring of headframe foundation of WOLONG LAKE coal mine industry squares.The paper introduces the basic principles and methods of settlement monitoring and builds headframe foundation subsidence monitoring net based on the example of WOLONG LAKE coal mine. The monitoring network consists of three kinds of points and three types of networks. Three periods of overall observations are used National second order leveling method for subsidence monitoring network. And secondary network lasts for 13 periods. Gravity datum is selected for datum network to analyse the stability of the datum point using mean spacing method. Primary control network is used classical adjustment and diversity test on the joint points. Subsidence changement curve is drew based on rigorous adjustment with the result that the maximum of the main and auxiliary shaft headframe foundations substructure settlement is 12.7mm and 13.9mm, settlement difference 2.9mm and 4.7mm. The paper also studies on the grey relational analysis between the water level change of the long-view holes and subsidence variation of headframe foundation. And the rusult is that there is relatively strong correlation between the long-view hole NO.2 and subsidence variation of headframe foundation.The paper discusses modelling principles and predicting methods of grey system analysis model and time series analysis model. Based on gray system theory, GM(1,1) equal-dimension and new-information model is built with the result that the maximum of predicting data residual error of the main and auxiliary shafts headframe foundations substructure settlement is 0.3mm and 1.1mm, mean 0.12mm and 0.20mm. The accuracy of model reaches the highest level. According to time series analysis theory, AR(p) model is built with the result that the maximum of predicting data residual error of the main and auxiliary shafts headframe foundations substructure settlement is 0.7mm and 1.4mm, mean 0.19mm and 0.31mm. According to the available data, grey system predicting model is more suitable for the project than time series predicting model.In the end, the paper writes a program designed to deal with settlement data and predict settlement monitoring using VB 6.0.