Research On On-line Monitoring System Of Operation State Of Mine Scraper Conveyor

Scraper conveyor is the core transportation equipment of modern coal mining face.It transports raw coal through a motor-driven scraper chain,and cooperates with hydraulic supports and shearers to complete coal mining and transportation tasks.Once the scraper conveyor has equipment failure,it will cause coal to block the roadway,which will have a very bad impact on the safety production of coal mines.Real-time monitoring of the operation status of the scraper conveyor is particularly important.Diagnosing the operating status of the scraper conveyor is realized by collecting and analyzing the relevant status parameter data of its driving device.Existing diagnostic methods use a single type of sensor,and most of them require physical lines to transmit data,which is difficult to install,and the actual power consumption is high;the monitoring target does not cover the entire driving device;it fails to build a complete fault diagnosis system;let alone The corresponding operating status monitoring system.This article first analyzes the operating principle of mining scraper conveyors and determines the types of faults that need to be monitored.Developed low-power wireless sensors based on ZigBee technology for temperature,liquid level,vibration acceleration and speed.It has the characteristics of small size,low power consumption and flexible installation,thereby increasing the reliability of the monitoring system.In order to analyze the data of multiple sensors in real time and effectively,this paper proposes a basic model of BP neural network mining scraper conveyor operating state monitoring,and on this basis,introduces genetic algorithms to improve the accuracy of neural network diagnosis and establish a multiple Fault diagnosis optimization model based on sensor data fusion.The optimized model inputs the sensor data of the driving device and outputs the common faults of the scraper conveyor,which realizes the online monitoring of the operation status of the scraper conveyor.In this paper,combined with the coal mining work environment,a monitoring system platform for the operation status of mining scraper conveyors is designed,which realizes the functions of sensor data collection,real-time display of monitoring information,data analysis,data management,system settings and control operations,forming a set of comparative Complete online monitoring system for the operation status of the scraper conveyor.Finally,verify and test the application of the monitoring system constructed in this article.Through comparative experiments,it is found that the diagnostic accuracy of the optimized model is higher than that of the basic model,increasing by 13.5%.At the same time,in the process of comparison with traditional monitoring methods,it is found that the diagnostic accuracy of the method proposed in this article is 20% higher than that of the traditional method.This paper establishes a monitoring model and a monitoring system for the operation status of the mining scraper conveyor,which scientifically and reasonably solves the problem of the difficulty of accurate and real-time diagnosis of the mine scraper conveyor failure.It provides a reasonable method for fault diagnosis of mining scraper conveyors,effectively reduces the management cost of mine equipment,and ensures the production efficiency and production safety of coal mines.