The main method of fault diagnosis of fag bearing

Asynchronous motor fag bearing fault detection and diagnosis methods, traditionally people are classified according to the state quantity used for monitoring and diagnosis, that is, according to the nature of the measured signals, mainly temperature method, oil sample analysis method, fag bearing Vibration signal analysis method and stator current signal analysis method f7埘.

The temperature method determines whether the fag bearing is working properly by monitoring the temperature at the fag housing. Temperature monitoring is sensitive to changes in load, speed and lubrication of fag bearings, especially for overheating of fag bearings caused by poor lubrication. Therefore, it is more effective for this occasion. However, when fag bearings have relatively minor faults such as early pitting, spalling, slight wear, etc., temperature monitoring is basically not reflected, and can only be detected by this method when the fault reaches a certain severity. Therefore, temperature monitoring is not suitable for so-called local damage failures such as pitting and partial spalling.

The oil sample analysis method is a method for judging the condition and failure of the fag bearing by taking out the oil sample from the lubricating oil used in the fag bearing and collecting and analyzing the size and shape of the metal particles in the oil sample. This method is only suitable for oil-lubricated shafting and not for grease-lubricated shafting. In addition, this method is susceptible to damage from particles that are not damaged by other non-fag bearings. Therefore, this method has great limitations.

The fag bearing vibration signal analysis method is to collect the time domain vibration signal of the fag bearing and transform it into the frequency domain through the vibration sensor installed in the fag bearing seat or the appropriate orientation of the box body, and then the frequency domain vibration signal and the inherent frequency domain of the fag bearing. The vibration characteristics are compared to determine if a fag bearing fault has occurred. Because it is suitable for various types of fag bearings, the signal testing and processing is simple and intuitive, and the diagnostic accuracy is quite high. Therefore, it has become the most widely used fault diagnosis method for fag bearings. However, it needs to be equipped with a vibration sensor on the fag bearing, which increases the investment and maintenance workload. Moreover, it is inconvenient to install a vibration sensor device on a motor in many cases, thus affecting its practicability.

Stator Current Signal Analysis (MCSA) is a non-intrusive fault detection method that has been successfully applied in the detection of asynchronous motor rotor bars and stator winding turn-to-turn faults. The literature [8] applies it to asynchronous motors. Fag bearing fault detection. Compared with the fag bearing vibration signal analysis method, the stator current signal is easier to extract, so the method is simpler and more practical, and is a future development trend. However, the stator current signal can reflect the characteristic frequency component of the fag bearing fault is small, and it is easily submerged by the fundamental frequency component and noise, and the fault feature quantity is extracted.