Open AccessResearch on Computer Algorithm of Mine Gas Release Source Location Based on Multi-source Sensor Fusion
Author(s) -
Jiangping Nan,
Xuezhen Dai
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/558/2/022027
Subject(s) - leakage (economics) , coal mining , algorithm , sensor fusion , node (physics) , engineering , computer science , coal , artificial intelligence , structural engineering , economics , macroeconomics , waste management
Aiming at the problem of gas leakage source difficult to locate or inaccurately located due to the air leakage phenomenon in the goaf of coal mines, this paper proposes a mine gas emission source location algorithm based on multi-source sensor fusion. Firstly, by analyzing the gas distribution law of the goaf in the fully mechanized caving face, the sensor observation model and the gas release source diffusion model of the mine goaf are established, and then the machine learning positioning algorithm is used to estimate the parameters of the gas release source in the goaf and according to the iterative calculation The coordinate positions of the estimated parameters are obtained. Finally, the data fusion of the wireless sensor target source sensing node and the cluster head node is used to achieve the precise positioning of the gas release source. The results show that: compared with other algorithms, machine learning algorithms have obvious advantages in positioning accuracy. This method can effectively solve the problem of difficulty in locating the gas release source due to the air leakage phenomenon, and then provide a reference basis for gas prominent warning and gas extraction in the goaf.