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Proper maintenance and preventive strategies are essential to minimize bearing wear, extend service life, and ensure reliable operation of machinery. This chapter outlines key measures that can significantly reduce the risk of premature bearing failure.
Use the appropriate type and grade of lubricant specified for the bearing and application conditions.
Maintain correct lubricant quantity and regularly replenish or replace lubricants to prevent contamination and degradation.
Employ clean lubrication systems and filters to avoid ingress of dirt and moisture.
Ensure bearings are installed using correct tools and methods to avoid misalignment, excessive force, or damage.
Avoid contamination during handling and assembly by maintaining a clean environment.
Follow manufacturer’s guidelines for fit tolerances and mounting procedures.
Implement scheduled inspections including vibration analysis, temperature measurement, and lubricant checks.
Use condition monitoring tools to detect early signs of wear or abnormalities.
Establish baseline data and trending to enable proactive maintenance.
Avoid excessive loads, shocks, or misalignment during operation to reduce stress on bearings.
Maintain proper machine alignment and shaft runout within specification.
Control environmental factors such as temperature, humidity, and contamination levels.
Equip bearings with appropriate seals or shields to prevent ingress of dust, dirt, and moisture.
Regularly inspect seals for damage or wear and replace as necessary.
Provide technical training for maintenance personnel on bearing handling, installation, and inspection techniques.
Promote awareness of bearing wear symptoms and proper maintenance practices.
Adopting comprehensive preventive measures encompassing lubrication, installation, monitoring, operating control, sealing, and training is fundamental to minimizing bearing wear and achieving reliable, long-lasting operation of machinery.
Effective monitoring of bearing wear is critical for predictive maintenance and reducing unexpected downtime. Advances in sensor technology and data analysis have enabled more precise, real-time condition monitoring of rolling bearings. This chapter introduces the main technologies and tools used to monitor bearing wear.
Vibration sensors detect characteristic frequencies associated with bearing defects such as inner and outer ring faults, rolling element damage, and cage defects.
Signal processing techniques like Fast Fourier Transform (FFT) help isolate defect signals from background noise.
Vibration trend analysis supports early fault detection and severity assessment.
AE sensors detect high-frequency stress waves generated by crack initiation and material deformation.
It is highly sensitive to early-stage defects before they become visible on vibration spectra.
AE monitoring complements vibration analysis for enhanced detection capability.
Temperature sensors monitor bearing operating temperatures to identify abnormal heat generation caused by increased friction or lubrication failure.
Infrared thermography and embedded sensors provide real-time thermal data.
Regular sampling and laboratory testing of lubricant detect wear debris, contamination, and lubricant degradation.
Techniques include ferrography, spectroscopy, and particle counting.
Ultrasonic sensors detect changes in bearing sound waves caused by defects or lubrication issues.
It is useful for condition assessment in noisy industrial environments.
Integrates multiple sensor inputs (vibration, temperature, AE, etc.) with data analytics and machine learning for predictive maintenance.
Provides real-time alerts and long-term trend analysis to optimize maintenance schedules.
Employing advanced bearing wear monitoring technologies significantly improves early fault detection accuracy, enabling cost-effective predictive maintenance and reducing unplanned downtime.
