Condition monitoring techniques: how faults are found
Traditional condition monitoring relies on a toolkit of established techniques. Vibration analysis detects imbalance, misalignment and bearing wear in rotating machinery. Thermography picks up abnormal heat patterns. Oil analysis reveals wear particles and contamination in lubricants, and ultrasound catches leaks and early bearing defects in noisy environments. Each works well, but each needs sensors, survey routes or samples taken at the machine.
Faraday Predictive takes a different route. Our electrical signature analysis (ESA), delivered through Model-Based Voltage and Current (MBVI) technology, detects the same mechanical and electrical faults from the switchgear, using the motor itself as the sensor. There is no equipment fitted to the machine, which makes motor condition monitoring practical for submerged, hazardous and hard-to-reach assets, and continuous rather than periodic.
| Technique |
What it detects |
Requires equipment on the machine? |
Continuous or periodic? |
Works for inaccessible assets? |
| Vibration analysis |
Imbalance, misalignment, bearing wear |
Yes, sensors or handheld readings |
Either |
Rarely |
| Thermography |
Abnormal heat, electrical hot spots |
Yes, camera line of sight |
Usually periodic |
No |
| Oil analysis |
Wear particles, contamination |
Yes, physical samples |
Periodic |
No |
| Ultrasound |
Leaks, early bearing defects |
Yes, at the machine |
Usually periodic |
No |
| MBVI electrical signature analysis |
Mechanical, electrical and operational faults, plus energy waste |
No, connects at the switchgear |
Continuous |
Yes |
Each traditional technique has its place, and reliability centred maintenance helps determine where. But for motor-driven rotating machinery, MBVI covers the widest range of faults with the least intrusion.
Want the detail? Read our guides to condition-based monitoring techniques and electrical signature analysis