| The real-time mine ventilation network solution is one of the core algorithms for intelligent mine ventilation.The air resistance coefficient is the most important known condition for network solving and the most important parameter for the digital twin of the ventilation system.The degree of mirror image between the air resistance coefficient and the actual underground condition and the timeliness of its acquisition is the key scientific and technical problems that need to be solved in the field of intelligent ventilation.To address the problem that the prediction results of mine air resistance coefficient prediction methods and the test results of traditional mine air resistance measurement methods have large errors and do not represent the real resistance characteristics of the shaft,and do not meet the needs of intelligent ventilation.The dissertation adopts a combination method of theoretical analysis,laboratory experiments and field industrial tests to carry out a series of researches on the basic theory and method of mine air resistance coefficient reconstruction,and realise the intelligent reconstruction of mine air resistance coefficient based on sparse roadway air volume and differential pressure of structures,which has important theoretical and practical significance for the construction of intelligent"brain"of mine intelligent ventilation system.A non-linear programming model for the reconstruction of mine air resistance coefficient with sparse roadway airflow,structure pressure difference observation and solution error as the objective was developed.The heterogeneous two-dimensional covariates of airflow error and structure differential pressure error are transformed into one-dimensional covariates by the linear weighting method,i.e.,the multi-objective programming problem is transformed into a single-objective programming problem.And the one-dimensional covariates are used as the adaptation values,and the optimal reconstructed values of air resistance coefficient are solved by the differential evolutionary algorithm.An experimental system of a two-input two-return UPVC ventilation network with 37 nodes,54 branches,353m in length,and 14 adjustable dampers was built.Using 16 air volume observation points and 14 structure pressure difference observation points,54 branch wind resistance coefficients of the experimental system were obtained by using the reconstructed model.By changing the opening and closing amounts of the dampers,the network solution of the corresponding states and the system observation point airflow test experiments were conducted respectively.The experiments show that the MRE,MAE,MSE,and RMSE of the solved and tested values of the observed point air volume are 5.89%,4.43×10-3m3/s,3.96×10-5m6/s2,and6.29×10-3m3/s,respectively,and the MRE,MAE,MSE,and RMSE of the solved and tested values of the observed point pressure difference are 7.37%,29.92 Pa,1916.75Pa,and 43.78Pa.The intelligent reconstruction method of mine air resistance coefficient is feasible and universal,and the accuracy of the model meets the engineering requirements of intelligent mine ventilation.Aiming at the characteristics of long testing period and large testing workload of traditional mine air resistance measurement methods,an intelligent and rapid determination technology of mine air resistance coefficient based on intelligent reconstruction method was developed.116 air volume observation points and 20 dampers pressure difference observation points were selected for the East-Central-West No.1 mining area with 495 branch roadways.By utilizing the air resistance coefficient intelligent determination method,the whole mine air resistance coefficient was measured and the MRE,MAE,MSE and RMSE were 8.63%,0.65m3/s,1.63m6/s2 and1.28m3/s respectively between the solved value and the observed point airflow test value using the measured air resistance coefficient.The measurement results were applied in the simulation of the emergency response to the collapse of the blind shaft in 33-row at Jinchuan Longshou Mine,and the emergency response scheme to temporarily activate the 10-row inclined shaft as a supplementary return shaft to increase the air supply to the mine was proposed.The relative error between the simulated and measured return air volume of the ventilation system after the main ventilation fan of the 10-row inclined shaft was put into operation was 3.23%,indicating that the measurement results were reliable and the timeliness and accuracy of the measurement method were verified in practice.The dissertation has 40 figures,13 tables,and 204 references. |
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