The frictional resistance coefficient of ventilation of a roadway in a coal mine is a very important technical parameter in the design and renovation of mine ventilation. Calculations based on empirical formulae and field tests to calculate the resistance coefficient have limitations. An inversion method to calculate the mine ventilation resistance coefficient by using a few representative data of air flows and node pressures is proposed in this study. The mathematical model of the inversion method is developed based on the principle of least squares. The measured pressure and the calculated pressure deviation along with the measured flow and the calculated flow deviation are considered while defining the objective function, which also includes the node pressure, the air flow, and the ventilation resistance coefficient range constraints. The ventilation resistance coefficient inversion problem was converted to a nonlinear optimisation problem through the development of the model. A genetic algorithm (GA) was adopted to solve the ventilation resistance coefficient inversion problem. The GA was improved to enhance the global and the local search abilities of the algorithm for the ventilation resistance coefficient inversion problem.

JO - Archives of Mining Sciences L1 - http://journals.pan.pl/Content/109021/PDF/Archiwum-63-4-02-Gao.pdf L2 - http://journals.pan.pl/Content/109021 PY - 2018 IS - No 4 EP - 826 KW - coal mine ventilation KW - ventilation coefficient KW - inversion KW - genetic algorithm A1 - Gao, Ke A1 - Deng, Lijun A1 - Liu, Jian A1 - Wen, Liangxiu A1 - Wong, Dong A1 - Liu, Zeyi PB - Committee of Mining PAS VL - vol. 63 JF - Archives of Mining Sciences SP - 813 T1 - Study on Mine Ventilation Resistance Coefficient Inversion Based on Genetic Algorithm DA - 2018.12.17 UR - http://journals.pan.pl/dlibra/docmetadata?id=109021 DOI - 10.24425/ams.2018.124977 ER -