Study On The Dynamic Safety Evaluation & Prediction Technology In Coalmine

As the basic industy of Chian's national economy, the coal industy was also a special industy with high safety risk, so the coal safety was the key-point to the continuous development of the coal industry. It was vital in both theory and practice to study how to control effectively safety risk in coal mines. In this paper, the home and abroad theories and technologies of safety evaluation were summarized, the dynamic safety evaluation and safety prediction models of coalmine were established. The models which have been established were used to deal with the coalmines that data have been collected from.The production system underground in coal mine was a disaster system which consists of the human-machinery-environment and the extremely complex horizons. The mechanism of the disasters was different, but the factors initiating the disasters were interrelated each other. The disasters may take place at any time and every where, and affected from one to others. According to the structure features of the calamity in coal mine, we have to take the assessment to the hazard degree of the system, and previously acquire the effect of the possible results of the accidents to the whole production system, so that the technology and management administrators can adopt the measures, and the aim of the safety production will be obtained. The key problem to the safety management and control was to find and establish the scientific and reasonable safety evaluation models, and to combine the models with the practice production. Many problems in the safety system in coal mine were non-linear. The traditional and the previously function-setting evaluation methods have appear their localization, and the problems of the fixing and changing weight could not also be solved perfectly.In the paper, the chinese coalmine safety status was analyzed to put forward the importance and necessity to use safety evaluation. The home and abroad safety evaluation were summarized to analyze the problems of traditional coal mine safety evaluation methods, the characteristic of artificial neural network (ANN) were analyzed, the significances, ideals, methods and main contents of this subject were proposed.Based on the accidental incidence theory and other safety theories, the analytic hierarchy process were combined with other methods to analyze the primary factors affecting coal mine safety, classified into 10 types including human, mechanical, environmental factors. Based on the requirements of the safety evaluation model, under the precondition and the principles of the constitution and quantity of the indicators, the mine safety evaluation indicators system was completely constructed, and the every mportant factor during the production processes was incarnated in the indicator system.Based on the structure characteristic of artificial neural network (ANN) and the mine safety evaluation indicators system which has been established, error back-propagation algorithm (BP) was chosen to deal with the mine safety evaluation model. The designs of network structure, the training process and the methods to improve the performance of the model were discussed. The neural network (NN) tool box and the graphical user interfaces (GUI) of the MATLAB software were introduced in order to use the powerful function of them to deal with the designs and training of the mine safety evaluation model. The foundation to use the mine safety evaluation model was laid.The mine safety evaluation model was designed by the use of the neural network (NN) tool box, trained by the means of safety sample data to prove that the model was applicable for mine safety evaluation. The results calculated were similar to the actual situation.The prediction was to search the future developing trend according to the history, also was the recognition to the future developing tendency. The aim of the prediction was that the processing measures can be done according to the developing and changing trend. It was very important to control effectively the safety in coal-mine for the mine production and operators. The effective control and management relied on the perfected and reliable process supervision, and the safety process control was rested with the pre-holding for the safety indexes of the coal-mine, therefore, the exact prediction was the precondition to pre-hold and take the effective technology and management steps. The safety prediction for the coal-mine was to forecast the future safe statue based on the past or present dangerous information of the system. According to the differentiating and analyzing relations between the macroscopical and microcosmic status, static and dynamic features, in this paper, the basic principals was determined for the safety prediction in the mine, and the mathematical models based on the artificial neural network and the non-linear gray system theory were established. The artificial neural network model was suitable to data-rich, and the GM (1, 1) was suitable to data-poor. Based on GM (1, 1), functional transformation grey model (1, 1) and UGM model were proposed and used to solution the insufficient of GM (1, 1) in short-time prediction. The models make the safety predicting results more objectivity and foreseeing.