Method to judge NTN bearing failure

First, look at its temperature

If the NTN bearing is in use and the environment in which it is used is very fixed, you can continuously record its temperature. If the temperature rises continuously or changes very irregularly, it means that there is a fault, and it is necessary to repair it in time .

Second, listen to its voice

People with a lot of professional experience can identify faults by sound. Only specialized personnel can hear the sound of the fault. You can also look at the lubricant. If it is dirty or there are foreign objects, come and see. Is it faulty, especially the large NTN bearings.

Third, vibration diagnosis technology

When the working surface of the bearing component has fatigue peeling, indentation or local corrosion, periodic pulse signals will appear during the operation of the bearing. This periodic signal can be received by a sensor (velocity type or acceleration type) installed on the bearing housing, and the fault of the bearing can be diagnosed through the analysis of the vibration signal.
Features: Vibration diagnosis technology is widely used; online monitoring can be realized; diagnosis is fast, and the diagnosis theory is mature.
Application range: Especially suitable for fault monitoring of bearings in rotating machinery.

Fourth, the performance of NTN bearing failure

NTN bearings may fail during operation. We can judge by this way, such as plastic deformation, non-operation or very slow rotation, etc. NTN bearings, shape change is the failure mode, and some NTN bearings that run very high, its heating is a way of failure.

Fifth, check regularly

Check regularly, and repair in time if there is a fault, so that it can be used normally during production, such as regular cleaning, checking the state of lubricating oil regularly, and rotating NTN bearings when cleaning. Let some of its hidden places be cleaned.

In fact, there are many ways to check NTN bearing failure besides disassembly, such as the above methods, but some identification methods require a lot of experience and are difficult to identify, so there are many Knowledge in this area.