Research On Flow Field Analysis And Temperature Compensation Of Thermal Anemometer For Mining

The mine ventilation system provides basic guarantee for safe production in the underground,and the accurate measurement and real-time perception of wind speed in the coal mine section is of great significance for intelligent decision-making and emergency control in the mine.In this thesis,a thermal anemometer is used to measure the underground wind speed at a single point and compensate it for the average wind speed at the cross-section.Aiming at the problem that the underground variable flow field and ambient temperature affect the accuracy of wind speed measurement,a velocity compensation correction point wind speed is proposed;And applying temperature compensation algorithms to reduce the impact of ambient temperature to achieve accurate measurement of thermal anemometers.Firstly,the operating principle of constant temperature difference and the convective heat transfer model of the thermal anemometer are introduced.The flow velocity distribution in the laminar and turbulent flow states of the flow field is analyzed theoretically.The reasons for the temperature drift phenomenon of the thermal anemometer are analyzed from the perspective of gas physical parameters and platinum resistance changing with temperature.Secondly,establish a three-dimensional model of the wind tunnel platform to simulate the real environment of the roadway.By using fluid simulation software,the wind measurement errors of anemometer probes at different insertion depths were compared and analyzed to find the best wind measurement location;The flow characteristics of the fluid under different wind speeds are further analyzed.The placement of the probe will affect the distribution of the flow field,and there are errors in the measurement results of point wind speeds.The wind speed was corrected by calculating the dynamic Reynolds number under turbulent flow conditions.The average absolute error of the wind speed after the velocity correction is 0.17 m/s,which decreases by 64.5% compared to the average absolute error of the wind speed before the correction,effectively reducing the impact of the flow field on the wind speed measurement.Thirdly,for the temperature drift phenomenon of thermal anemometers,a generalized regression neural network(GRNN)is used for temperature compensation,and a dragonfly algorithm(DA)is introduced to optimize the smoothing factor of GRNN.Due to the shortcomings of DA that are prone to fall into local optimal solutions and slow search speed,Singer chaotic mapping strategy is introduced to increase the randomness of population initialization;Adopting a nonlinear decreasing strategy to improve the step vector improves the optimization accuracy and convergence speed of the algorithm;Adopting a dimensionally greedy update strategy improves the quality of the solution and improves the local search ability of the algorithm.Based on IDA optimization of GRNN parameters,an IDA-GRNN temperature compensation model was established.Finally,combined with the safety requirements under the mine,a thermal anemometer for mining was designed,and a circular wind tunnel experimental platform was built to conduct temperature characteristics tests on the thermal anemometer.The IDA-GRNN was validated with the obtained wind speed data.The results show that after IDA-GRNN temperature compensation,the maximum fiducial error of the thermal anemometer in the range of 0 m/s to 15 m/s is 0.73%,and the average absolute error is 0.05 m/s,which meets the accuracy requirements for wind speed measurement in the mine ventilation system.This thesis includes 50 figures,14 tables,and 94 references.