Aiming at the problem that the Local mean decomposition(LMD) method is difficult to draw early weak fault,a fault diagnosis method for the roller bearing based on maximum correlated kurtosis deconvolution(MCKD) and LMD was proposed.Firstly,the fault signal was de-noised and meantime periodic impact components were enhanced by MCKD method,Then,that result is decomposed by LMD to get PF,the correlation coefficient between the PF and the signal is used as the standard of judgment,so that the redundant low-frequency PF can be rejected.Finally,the effective PF is selected to analyze the spectrum and extract the fault feature.The experiment of the simulation data and the actual roller bearing fault diagnosis data show that the method can effectiv...
Aiming at the fact that the vibration signal of rolling bearing would exactly display non-stationary...
Detecting periodic impulse signal (PIS) is the core of bearing fault diagnosis. Earlier fault detect...
When rolling bearings fail, it is usually difficult to determine the degree of damage. To address th...
In order to improve the diagnosis accuracy and solve the weak fault signal of rolling element of rol...
The early fault characteristics of rolling element bearings carried by vibration signals are quite w...
Compared with the strong background noise, the energy entropy of early fault signals of bearings are...
A novel bearing vibration signal fault feature extraction and recognition method based on the improv...
When refiner gearbox has incipient failure,its vibration signal,with hidden impulse component veiled...
A rolling element signal has a long transmission path in the acquisition process. The fault feature ...
Aiming at the impact feature in fault signals of the rolling bearings,The improved algorithm diagnos...
For the problem of Local Mean Decomposition( LMD) was easily affected by noise interference when in ...
Aiming at the no stationary characteristic of a gear fault vibration signal,a method based on Ensemb...
Vibration analysis is one of the main effective ways for rolling bearing fault diagnosis, and a chal...
In response to the problem that nonlinear and non-stationary rolling bearing fault signals are easil...
The fault frequencies are as they are and cannot be improved. One can only improve its estimation qu...
Aiming at the fact that the vibration signal of rolling bearing would exactly display non-stationary...
Detecting periodic impulse signal (PIS) is the core of bearing fault diagnosis. Earlier fault detect...
When rolling bearings fail, it is usually difficult to determine the degree of damage. To address th...
In order to improve the diagnosis accuracy and solve the weak fault signal of rolling element of rol...
The early fault characteristics of rolling element bearings carried by vibration signals are quite w...
Compared with the strong background noise, the energy entropy of early fault signals of bearings are...
A novel bearing vibration signal fault feature extraction and recognition method based on the improv...
When refiner gearbox has incipient failure,its vibration signal,with hidden impulse component veiled...
A rolling element signal has a long transmission path in the acquisition process. The fault feature ...
Aiming at the impact feature in fault signals of the rolling bearings,The improved algorithm diagnos...
For the problem of Local Mean Decomposition( LMD) was easily affected by noise interference when in ...
Aiming at the no stationary characteristic of a gear fault vibration signal,a method based on Ensemb...
Vibration analysis is one of the main effective ways for rolling bearing fault diagnosis, and a chal...
In response to the problem that nonlinear and non-stationary rolling bearing fault signals are easil...
The fault frequencies are as they are and cannot be improved. One can only improve its estimation qu...
Aiming at the fact that the vibration signal of rolling bearing would exactly display non-stationary...
Detecting periodic impulse signal (PIS) is the core of bearing fault diagnosis. Earlier fault detect...
When rolling bearings fail, it is usually difficult to determine the degree of damage. To address th...