Research On High Precision Temperature Compensation Technology Of Mine Wind Pressure Sensor

The accurate measurement of mine ventilation resistance is an important part of mine ventilation and safety management,and is of great relevance to the fault diagnosis,optimization and emergency control of mine ventilation systems.As an important piece of equipment for mine safety and metrology management,piezoresistive wind pressure sensors are widely used for differential pressure monitoring in mines.However,in practice,piezoresistive wind pressure sensors are often affected by the ambient temperature and require appropriate measures to compensate and correct for temperature drift.In order to solve the problem that wind pressure sensors are prone to temperature drift,this thesis investigates the temperature characteristics of wind pressure sensors and designs an intelligent algorithm for temperature compensation to improve the measurement accuracy of wind pressure sensors.Firstly,this thesis introduces the working theory and internal structure of the wind pressure transducer,and conducts an in-depth study on the causes of the temperature drift phenomenon of the wind pressure transducer,focusing on the problems of zero point drift and sensitivity drift,summarizing the commonly used temperature dump compensation methods and analyses the advantages and drawbacks of each.Secondly,following the design principles of intrinsic safety and interference immunity,the overall design of the wind pressure sensor was proposed and the important components were selected.After the sensor design and fabrication,an experimental system platform is built to conduct temperature characteristics experiments and obtain relevant experimental data to provide training samples for the subsequent temperature compensation algorithm.Thirdly,the temperature drift phenomenon of the piezoresistive wind pressure sensor is compensated for by means of a support vector regression model(SVR).Since the selection of the penalty parameter C and the kernel function parameter gamma have a large impact on the prediction effect of SVR,this thesis introduces Cubic chaotic mapping,adaptive parameter control and the Corsi-Gaussian variational strategy for multi-strategy improvement of the sparrow search algorithm(Multi-strategy Sparrow Search Algorithm,MSSA)for the optimal parameter selection of SVR.The MSSASVR temperature compensation algorithm is validated by simulation with experimental data.The simulation results show that the maximum quoted error of the wind pressure sensor after compensation by the algorithm decreases from 8.6% to 0.84% and the sensitivity drift coefficient is reduced by one order of magnitude,indicating that the temperature compensation algorithm plays a good role in suppressing the temperature drift of the wind pressure sensor.Lastly,the temperature compensation algorithm was transplanted into the wind pressure sensor and tested on a temperature experimental platform.Finally,the temperature compensation algorithm was transplanted into the wind pressure sensor and tested on a temperature experimental platform.The wind pressure sensor was tested to have a maximum error of 1.6 Pa in the range of 0 to 40°C.The test results show that the wind pressure sensor is able to meet the demand for accurate measurement of wind pressure under the influence of ambient temperature.This thesis has 42 figures,11 tables and 94 references.