Add to ORKGBearings are widely used in rotating machines. Its health status is a significant index to indicate whether machines run continually or not. Detecting the bearing defects timely is very important for the maintenance decision making. In this paper, a novel bearing defects detection method based on EMD and Fractal Dimension is developed. The original data is decomposed into a set of intrinsic mode functions (IMFs) using EMD, and the fractal dimension of IMFs which contains bearing fault characteristic information are calculated, and these characteristic parameters are used to identify bearing fault types. The effectiveness of this methodology is demonstrated using experimental data
Nowadays, the fault diagnosis of rolling bearing in aeroengines is based on the vibration signal mea...
The condition monitoring technology and fault diagnosis technology of mechanical equipment played an...
The health condition of rolling bearing can directly influence to the efficiency and lifecycle of ro...
Nonlinear characteristics are ubiquitous in the vibration signals produced by rolling element bearin...
Vibration signals acquired from bearing have been found to demonstrate complicated nonlinear charact...
Bearings are one of the critical components of any mechanical equipment. They induce most equipment ...
Abstract. Most rotating-machine failures are often linked to bearing failures. Proper condition moni...
Bearing failure is one of the dominant causes of failure and breakdowns in rotating machinery, leadi...
International audienceIn bearing fault diagnosis, ensemble empirical mode decomposition (EEMD) is a ...
In order to achieve the bearing fault diagnosis so as to ensure the steadiness of rotating machinery...
Dimensionless index as a new theory tool has been applied in fault diagnosis study, which has shown ...
Aiming at the fact that the vibration signal of rolling bearing would exactly display non-stationary...
As an important part of rotating machinery, bearings play an important role in large-scale mechanica...
Roller bearings are the most widely used and easily damaged mechanical parts in rotating machinery. ...
Faults in rolling element bearings often cause the breakdown of rotating machinery. Not only the fau...
Nowadays, the fault diagnosis of rolling bearing in aeroengines is based on the vibration signal mea...
The condition monitoring technology and fault diagnosis technology of mechanical equipment played an...
The health condition of rolling bearing can directly influence to the efficiency and lifecycle of ro...
Nonlinear characteristics are ubiquitous in the vibration signals produced by rolling element bearin...
Vibration signals acquired from bearing have been found to demonstrate complicated nonlinear charact...
Bearings are one of the critical components of any mechanical equipment. They induce most equipment ...
Abstract. Most rotating-machine failures are often linked to bearing failures. Proper condition moni...
Bearing failure is one of the dominant causes of failure and breakdowns in rotating machinery, leadi...
International audienceIn bearing fault diagnosis, ensemble empirical mode decomposition (EEMD) is a ...
In order to achieve the bearing fault diagnosis so as to ensure the steadiness of rotating machinery...
Dimensionless index as a new theory tool has been applied in fault diagnosis study, which has shown ...
Aiming at the fact that the vibration signal of rolling bearing would exactly display non-stationary...
As an important part of rotating machinery, bearings play an important role in large-scale mechanica...
Roller bearings are the most widely used and easily damaged mechanical parts in rotating machinery. ...
Faults in rolling element bearings often cause the breakdown of rotating machinery. Not only the fau...
Nowadays, the fault diagnosis of rolling bearing in aeroengines is based on the vibration signal mea...
The condition monitoring technology and fault diagnosis technology of mechanical equipment played an...
The health condition of rolling bearing can directly influence to the efficiency and lifecycle of ro...