Study On Fault Diagnosis Of Gear And Bearing Of Coal Mine Machinery

Aiming at the gear and bearing of coal mime machinery, this paper briefly described thepurpose and significance of their fault diagnosis, as well as the research status anddevelopment trends of diagnostic technology, analyzed the common fault types and causes.Besides, as to gears, the signal features of typical fault and the common signal processingmethods used in fault diagnosis have been discussed in detail.Given the problems such as low speed, overloading and poor environment, which areexisted in the transmission system of coal mine machinery, this paper mainly studied thevibration mechanism and failure mechanisms of gear and rolling bearings, regarding the gearand bearing under low speed and overloading environment as research objects. Then thesignal processing methods, such as vibration analysis in time domain, spectrum analysis,power spectrum analysis and wavelet analysis and so on, have been combined. In addition,the signal demodulation technology and the method of sideband analysis were applied intofault diagnosis of gear and bearing to extract the fault features.Neural Network, which is used in complex systems, has been studied in this paper,discussing the basic principles and the process of modeling. Additionally, the fault sensitiveparameters of gear box, as the input of network, were extracted by using traditional signalprocessing methods. After learning and training of BP network, the fault classification of gearbox was realized, and also the results of classification has been well obtained, which Provideda theoretical basis for the intelligent diagnosis of gear fault. Finally, this study showed thatapplying the method into fault diagnosis of mining machines will have great values.