Research On Fault Monitoring And Safety Warning Methods For Mine Ventilators

Mine ventilator is an important mechanical and electrical equipment in mine safety production.It undertakes the functions of supplying fresh air,discharging harmful gas,adjusting underground temperature and humidity,etc.Mine ventilator fault monitoring and warning are of great significance for ensuring personnel life safety,improving equipment utilization ratio and optimizing equipment operation and maintenance.The current fan fault monitoring methods still face challenges in information acquisition,data analysis,early warning linkage,and are difficult to meet the development needs of intelligent emergency.In order to promote the informatization of emergency management and further improve the ability of equipment monitoring and early warning,it is necessary to study the rules and methods of mine ventilator fault monitoring and safety early warning under emergency mode.Firstly,the basic theory of mechanical fault diagnosis of mine ventilator is studied,including the type,cause and characteristics of typical mechanical fault,vibration signal analysis technology,common methods of fault diagnosis,etc.,which lays a solid foundation for subsequent research.Then,a fault monitoring and safety early warning system based on emergency mode is designed,the concept and characteristics of emergency detection mode are defined,and the components,key technologies and warning strategies of fault monitoring system based on emergency mode are analyzed.Then,the intelligent vibration detector facing emergency is mainly studied,and the overall analysis and software and hardware design of the detector are completed.The vibration detector uses non-contact optical sensing technology and Bluetooth wireless communication technology to solve the problem of vibration information free and efficient acquisition in emergency mode.Next,explore emergency-oriented fault analysis and safety early warning strategies,extract high-precision vibration data adaptively based on Kalman filter algorithm,and adopt improved FFT vibration spectrum analysis method and trend-based vibration fault early warning model to reliably and effectively solve the problem of vibration fault identification and early warning.Finally,an experimental platform is built and experimental research is carried out.The results show that the method proposed in this dissertation effectively improves the flexibility,accuracy and intelligence level of vibration signal detection,provides a perfect technical solution for vibration monitoring and fault warning in emergency mode,and has good application and promotion value for promoting emergency informatization.There are 67 pictures,20 tables and 92 references in this paper.