Study On Monitoring And Health Assessment Method And System Of Mine Main Ventilator

Mine main ventilator is an indispensable and important equipment in coal mine safety production.Once abnormal,it will pose a great threat to the coal mine production and the safety of underground personnel.Effective monitoring and health status assessment of mine main ventilator is an important guarantee for the safety of mine ventilation and scientific maintenance.This paper takes the mine main ventilator as the object,studies its main parameter test method and health state evaluation method,and develops the monitoring and evaluation system based on this.The research of this paper has important practical significance to improve the mine main ventilator monitoring and health state evaluation level,and to ensure the mine ventilation safety production.Main research contents and results of this paper:(1)Determine the operation state monitoring parameters of the mine main ventilator,and study the main parameter test method.For air volume of the methods used currently in the problem of measuring error caused by the installation method,established the simulation model of three kinds of common wind adit analysis sensor installed wind flow distribution caused by the change rule,get the sensor mounting bracket cross-section wind flow distribution changes drastically,influence of the scaffold forepoling section after 200 mm,the wind speed distribution in uniform,effect is reduced,The influence of advanced support at 250 mm is minimal.Taking square air tunnel as an example,the experimental verification results show that:in the selected eight working points,the measurement error of the sensor probe installed at the bracket section is the largest,and the measurement error at 250mm is the smallest,which can be used as the reference location for the sensor probe installation.(2)The evaluation and application of multivariate state estimation method on the health state of mine main ventilator are studied.The principle of multivariate state estimation algorithm is analyzed,and the algorithm is applied to the health state evaluation of the main ventilator.Taking the No.2 main ventilator of Shaanxi Binchang Xiaozhuang Mining Co.,Ltd.as an example,reasonable variables are selected to establish the health state evaluation model of the mine main ventilator.The validity of the model was verified by using the monitoring data of the normal operation of the fan,and the estimated values of various variables were obtained.Compared with the observed values,the results show that the estimation accuracy of the MSET model is high,and it can meet the requirements of the health assessment of the main fan.(3)The monitoring and health condition evaluation system of mine main ventilator has been developed.A hardware platform based on PXI bus is built,which is composed of NI PXIe-1062Q&NI PXIe-8106 host as the core,NI PXIe-6259 data acquisition card,vibration,temperature and humidity,pressure,wind speed,voltage and current sensors.Taking LabVIEW2017 as the development platform,and using component-oriented and process-oriented programming methods,the monitoring program of vibration,temperature,air pressure,air volume and motor power of mine main ventilator,the evaluation program of fan health status,data storage and playback and other programs are developed.(4)An experimental platform was built to verify the vibration,temperature,air pressure,air volume monitoring functions and data storage and playback functions of the mine main ventilator monitoring system.The experimental results show that the system can meet the real-time monitoring requirements of the main ventilator operating state.The health evaluation effect of the MSET model and the health evaluation function of the system were verified by the operation data of the No.2 main ventilator of Shaanxi Binchang Xiaozhuang Mining Co.,Ltd combined with the abnormal vibration data of DHVTC vibration test platform.The results show that:When the vibration velocity value exceeds 2.07mm/s,the model starts the health warning,which indicates that this method can effectively warn the fault information of the mine main ventilator and the health evaluation module of the system can also realize the function of evaluating the health state of the fan.