The Problem: Bearing Failure in a Locomotive Alternator
A major rail operator, faced a critical maintenance issue with the alternator bearings in one of their locomotives. The train experienced unusual vibration and noise, suggesting potential bearing failure. Left unresolved, this failure could have led to a catastrophic breakdown, causing operational delays and significant repair costs.
Cost of Inaction: Without early detection, the bearing defect could have caused total alternator failure, requiring costly unplanned maintenance, locomotive downtime, and revenue loss from service disruption.
The Solution: Advanced Diagnosis Using VibCloud
- Data Collection: Technicians collected vibration data using the VibCloud mobile app. The app guided them step-by-step, ensuring consistent measurements.
- Data Analysis:
- Initial Indicators: The acceleration time waveform showed repeating impact spikes, suggesting metal-to-metal contact. A rumbling noise was confirmed via audio playback from the vibration recording.
- Demodulation Analysis: VibCloud’s automated demodulation detected impacts occurring 7.7 times per shaft revolution. Sideband analysis revealed frequency spacing matching the rotational speed, indicating inner race bearing damage.
- Severity Confirmation: A velocity spectrum confirmed the presence of harmonic peaks linked to bearing faults, indicating advanced damage.
- Recommended Action: The analysis concluded with high confidence that the inner race of the bearing was severely deteriorated. Immediate replacement was recommended to prevent further damage and ensure operational reliability.
Key Benefits of Using VibCloud
- Accurate Fault Diagnosis: VibCloud’s advanced algorithms pinpointed the exact cause of the problem.
- Preventive Maintenance Insight: The system’s data-driven approach enabled proactive maintenance, avoiding costly breakdowns.
- Operational Continuity:Rail operator maintained uninterrupted service, saving on emergency repairs and service delays.
This case highlights VibCloud’s powerful diagnostic capabilities in condition monitoring. By detecting and diagnosing bearing damage early, rail operator avoided a potential operational crisis, emphasising the importance of predictive maintenance for asset-intensive industries.
