Analysis of data mining of clustering and its application to mechanical transmission fault diagnosis

For mechanical fault in the gear transmission system difficult to diagnosis,an improved clustering method was presented based on the DBSCAN(Density-based spatial clustering of application with noise) by using the concept of grid processing.The faults of gear transmission system were detected and the styles of gear faults were estimated by the improved clustering method,which also calculated spectral entropy of vibration signal of gear transmission at different rotate speed,and showed the spectral entropy distribution in Two-dimension and Three-dimension domain by grid plotting.So it enables better clustering and identification of gear faults such as natural,cracked and attrited faults,etc.The method is verified experimentally to be capable of distinguishing reliably gear transmission signals at different work conditions for gear transmission system,with clustering rate up to 96%.It indicates that the method is feasible for classification and diagnosis of gear faults.