Research On Fault Diagnosis Of Gears And Bearings Of Coal Mine Machinery

In this paper,the fault diagnosis of gear and bearing related components in coal mine machinery transmission system is studied.Through the relevant information,the development history and current situation in this field at home and abroad are understood,the shortcomings of the current fault detection and analysis system are analyzed,and the adjustments and changes that should be given in the future research work are discussed.Coal mine is a low-speed mechanical transmission device,and heavy vehicles work normally in harsh environment,so the vibration mechanism and failure mechanism of gear system and rolling bearing need attention.The research object of this paper is the internal gears and bearings of coal mining machinery system working under this condition.Various signal processing methods can be used,such as time domain vibration analysis,frequency spectrum analysis,power spectrum analysis,wavelet analysis and so on.This paper focuses on the spectrum analysis,establishes the model corresponding to the fault and vibration signal,and realizes the automatic matching and calculation of the model,and designs the artificial neural network system.On the basis of the neural network modeling,the sensitive parameters of gearbox fault are taken as the input information of the network model.The BP neural network is used to simulate the multi fault state of the gearbox,so as to achieve better classification results for the fault diagnosis of gears and bearings.After analyzing the fault types and causes of gears and bearings of coal mining machinery,the vibration signal is taken as the basis of fault detection,and the frequency domain analysis method is used to determine the fault type of coal mining machinery,which simplifies the analysis process.Research shows that the method of this study is suitable for fault diagnosis of coal mining machinery,and has important practical value.Figure[30]table[5]reference[81]...