矿井主通风机是煤矿安全生产不可缺少的重要设备，一旦出现异常，会对煤矿生产和井下人员的安全造成巨大威胁，对其进行有效的监测、健康状态评估以及科学维护是矿井通风安全的重要保证。本文以煤矿主通风机为对象，研究其主要参数测量方法和健康状态评估方法，并基于此开发了监测与评估系统，论文研究对提高矿井主通风机监测和健康状态评估水平，保证矿井通风安全生产具有重要的现实意义。

论文主要研究内容和取得结果：

（1）确定矿井主通风机运行状态监测参数，对主要参数测试方法进行研究。针对风量目前采用的方法中因安装方式造成测量误差大的问题，建立了常见三种风硐的仿真模型，分析传感器安装所造成的风流分布变化规律，得到传感器安装支架截面处受支架干扰风流分布变化剧烈，超前支架截面200mm后，风速分布趋于均匀，影响减小，超前支架250 mm影响最小。以方形风硐为例进行实验验证，结果表明：在选取的8个工况点，传感器测头安装在支架截面处测量误差均最大，250mm处最小，此处可作为传感器测头安装参考位置。

（2）研究多元状态估计法对矿井主通风机健康状态的评价和应用方法。分析多元状态估计算法原理，将该算法应用到主通风机健康状态评估，以陕西彬长小庄矿业有限公司2#主通风机为例，选取合理的变量，建立矿井主通风机健康状态评估模型。利用风机正常工作时的监测数据对模型的有效性进行验证得到各变量估计值，并与观测值对比，结果表明MSET模型估计精度高，可以满足主通风机健康评估的要求。

开发了矿井主通风机监测与健康状态评估系统。构建了基于PXI总线，以NI PXIe-1062Q & NI PXIe-8106主机为核心，NI PXIe-6259数据采集卡，振动、温湿度、压力、风速、电压和电流传感器组成的硬件平台。以LabVIEW2017为开发平台，采用面向组件和面向过程的程序设计方法，开发了矿井主通风机振动、温度、风压、风量及电机功率监测程序，风机健康状态评估程序，数据存储回放等程序。

搭建实验平台，对矿井主通风机监测系统的振动、温度、风压、风量监测功能和数据存储回放功能进行验证，实验结果表明系统可满足主通风机运行状态实时监测的需求。以陕西彬长小庄矿业有限公司2#主通风机运行数据结合DHVTC振动实验台的振动异常数据对MSET模型健康评估效果和系统健康评估功能进行验证，结果表明：当振动速度值超过2.07mm/s时模型就开始健康预警，表明该方法可以有效地对矿井主通风机的故障信息进行预警并且系统健康评估模块也可以实现对风机健康状态的评估功能。

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.

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.

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.

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