Can a deep groove ball bearing be detected for abnormalities by establishing a baseline vibration level while it is operating?

Deep groove ball bearings can detect any abnormalities by establishing a baseline vibration level during operation. Vibration monitoring is an effective method for early detection of bearing problems and potential faults. Establishing a baseline vibration level can provide reference for subsequent vibration analysis and help detect anomalies in a timely manner. The following are several key steps and points for establishing a baseline vibration level for detection:

1. Initial vibration data collection
Under normal working conditions of the bearing, it is necessary to first collect vibration data for a period of time, which should be collected under fault free and normal operating conditions as baseline data.
When collecting data, it is necessary to ensure stable working conditions, including load, speed, temperature, etc., and minimize the interference of environmental factors to ensure the accuracy of baseline data.

2. Choose appropriate measuring tools and sensors
Vibration sensors (such as accelerometers) should be installed correctly at critical positions on bearings, usually on the outer ring or supporting components of the bearing.
Suitable frequency range and sensitivity can be selected as needed to ensure the capture of the vibration characteristics of the bearing.

3. Baseline vibration level setting
The baseline vibration data should record information such as frequency, amplitude, and waveform during normal operation.
By analyzing these data, determine the vibration range during normal operation and set a safe vibration baseline level.
The baseline level usually includes the range of vibration amplitude, frequency characteristics, harmonic signals, etc.

4. Real time vibration monitoring and comparison
During normal operation of the equipment, real-time monitoring of vibration data is conducted and compared with the set baseline.
If there is a significant deviation or a change in frequency components (such as an increase in high-frequency vibration, a sudden change in low-frequency vibration, etc.), it may indicate that there is a problem with the bearing or other components.

5. Abnormal recognition and diagnosis
When abnormal vibration data occurs, diagnosis can be made by combining vibration characteristics from different frequency ranges.
For example, if the vibration frequency is related to the rolling element frequency, raceway frequency, etc. of the bearing, it may indicate that the bearing has been damaged or worn.
By comparing baseline data, issues such as bearing wear, damage, and insufficient lubrication can be quickly identified.

6. Long term tracking and maintenance
Continuously monitor vibration changes, regularly collect vibration data, and compare it with the baseline to ensure that the equipment always operates in a healthy state.
For devices that are found to be abnormal, timely inspection, maintenance, or replacement of bearings can be carried out to avoid more serious malfunctions.

7. Set alarm threshold
Based on baseline vibration data, alarm thresholds can be set. When the vibration amplitude exceeds a certain level or abnormal frequency components occur, the system can automatically issue an alarm.
This can achieve early fault warning, reduce downtime and production losses.