Bearing damage diagnosis method to judge, people traditionally based on the amount of state monitoring and diagnostic classification in accordance with the nature of the signal of the measurements taken to classify major temperature Act, oil sample analysis, bearing vibration signal analysis by monitoring the temperature of the bearing at the stator current signal analysis h-el0 temperature method to determine whether the bearing operating normal. Reflects the changes of the temperature monitoring on the bearing load, speed, and lubrication is more sensitive, especially caused by the poor lubrication bearing is very sensitive to overheating. Therefore, for this case is more effective. However, when the bearing, such as early pitting, spalling, slight wear of a relatively minor failure, the temperature monitoring is substantially not reflected, only when the failure to reach a certain severity, with this ways can be detected. Therefore, temperature monitoring does not apply to so-called partial damage failure pitting local spalling.
The oil sample analysis method is a method to remove the oil sample, from the bearing lubricant used by the collection and analysis of the size and shape of the metal particles in the oil sample to determine the method of bearing operating conditions and faults. This method only applies to oil lubrication shafting, does not apply to a greased shafting. In addition, this method is susceptible to the influence of the other non-bearing damage falling particles. Therefore, this approach has serious limitations.
Bearing vibration signal analysis method is the acquisition the bearing time domain vibration signal and converts it to the frequency domain by the vibration sensor mounted on the bearing housing or casing proper orientation, and thus will be inherent in the vibration characteristics of the frequency domain to frequency domain vibration signal with the bearing for comparison , to determine the bearing fault occurred. Applicable to all types of various conditions bearing signal testing and treatment is simple, intuitive, very high accuracy of the diagnostic results, and thus become the most widely used bearing fault diagnosis method. But it need to be installed on the bearing vibration sensor, which increases the investment and maintenance workload. And vibration sensors installed in the motor equipment, in many cases, quite inconvenient and thus affect its practicality.
Stator current signal analysis (MCSA) is a non-intrusive fault detection method has been successfully applied to the induction motor broken rotor bars and stator winding inter-turn short circuit fault detection, and its application to induction motor bearing fault detection in . Relative bearing vibration signal analysis, the stator current signal is easier to extract, and thus, this method is more simple and practical, is the future development trend. Stator current signal can reflect the characteristics of the bearing failure frequency component amplitude is small, easily overwhelmed by the fundamental frequency component and noise, to the amount of fault features extraction with


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