What are the key points of daily maintenance and care of Mining Electric Motor?

1. Cleaning and dust prevention
Regularly clean the dust and dirt on the surface of the motor to prevent dust from entering the inside of the motor.
Ensure that the vents are unobstructed to avoid blockage that affects heat dissipation.
2. Check the wiring
Check the motor terminals frequently to ensure that the wiring is firm and there is no looseness or oxidation.
Check whether the cable sheath is damaged or cracked to prevent short circuit or leakage.
3. Temperature monitoring
Use a temperature measuring instrument to regularly measure the temperature of the motor during operation, especially the bearings and windings.
If the temperature rises abnormally, stop the machine in time to check the cause.
4. Lubrication and maintenance
Add or replace the appropriate amount of lubricating oil (grease) for the bearings at the prescribed time interval.
Check the quality of the lubricating oil (grease), and replace it in time if it deteriorates.
5. Vibration inspection
Feel the vibration of the motor during operation. If there is abnormal and severe vibration, check whether the motor is installed firmly and whether the internal components are loose or damaged.
6. Insulation detection
Regularly use an insulation resistance tester to detect the insulation performance of the motor to ensure that it meets safety requirements.
For motors with reduced insulation performance, repair or replace them in time.
7. Regular inspections
Listen to the sound of the motor when it is running to see if there is any abnormal noise.
Observe whether the motor speed is stable and whether the current and voltage are normal.
8. Moisture-proof treatment
In a humid mining environment, take moisture-proof measures, such as using moisture-proof agents, heating devices, etc.
9. Spare parts management
Reserve necessary wearing parts, such as bearings, brushes, etc., for timely replacement.
10. Recording and analysis
Establish maintenance records for motors, including inspection time, maintenance content, problems found and treatment methods, etc.
Analyze the data to discover potential problems and patterns in advance.