Research On Fault Diagnosis System Of Coal Mine Main Fan

Main fan is one of the important equipment in the safe production of coal mine.It has the function of diluting gas and other harmful gases and regulating underground climate temperature.Therefore,in order to ensure the reliable operation of the coal mine main fan,fault diagnosis plays an extremely important role,which can provide favorable guarantee for creating a good downhole production environment,ensuring personnel safety and normal operation of other equipment.This paper mainly studies the new method of extracting the characteristic value of the signal of the main fan of coal mine and fault diagnosis,and solves the problems of noise interference and identification difficulty in the traditional methods,so as to improve the accuracy of extracting the characteristic value and diagnosis accuracy.The main research contents are as follows:Firstly,taking the mechanical fault diagnosis of coal mine main fan as the research background,the development status of fault diagnosis technology at home and abroad is summarized,and the research status of fault diagnosis technology of coal mine main fan at home and abroad is emphatically analyzed.Based on the structural characteristics and main components of the main fan in coal mine,the mechanical faults of the fan are analyzed and studied,and the signal characteristics of different fault types are extracted and summarized.Secondly,based on the data collected in the experiment,the processing method is studied according to the signal characteristics.The Empirical Mode Decomposition(EMD)method can reflect the local characteristics and physical changes of signals,and there is the problem of modal aliasing.On the basis of EMD,the CEEMD method is proposed to eliminate some modal aliasing and residual noise.In order to extract features more accurately,Independent Component Analysis(ICA)method is introduced to effectively improve the accuracy of signal extraction and processing,and CEEMD combined with ICA is taken as the extraction method of fault features.On this basis,the fault diagnosis system of coal mine main fan is studied and designed,and the system is implemented.Finally,a fan test stand was built to simulate three faults of fan rubbing,loosening and eccentricity.The fault diagnosis system of the main fan of the coal mine was used to monitor and diagnose the simulated fan.When a fault occurs,the system can alarm in time and accurately,at the same time,the fault information is stored in real time,and the feature database of the wind turbine is continuously improved through learning,which fully verifies the effectiveness andfeasibility of the system.Then conduct field experiments,apply the fault diagnosis system of the main fan of the coal mine to actual production,and realize the equipment fault diagnosis through data collection,processing and self-learning.The system has certain practical application value.