Predictive Maintenance Case Study: Real-World Vibration, Infrared, Oil, and Motor Current Analysis

The following case studies showcase real data analyzed by the author, illustrating how predictive maintenance tools—vibration analysis, infrared thermography, oil analysis, and motor current analysis—detect faults early and extend equipment life.

Each example is presented as a frequency spectrum, and where relevant, as a time‑waveform, providing concrete evidence of faults in specific data segments.

Oil cleanliness reports identify dirty oil conditions, referencing ISO cleanliness levels as benchmarks. Maintaining oil quality is essential for preventing premature component failure and maximizing uptime.

Infrared thermography images reveal temperature variations across equipment components. Even subtle deviations can signal underlying issues, making trained personnel in thermographic interpretation highly valuable.

Electric motors, critical to manufacturing operations, commonly fail due to bearing wear or winding insulation breakdown. Motor current analysis can predict winding failures, enabling proactive maintenance schedules.

Vibration Data (Gear Mesh) Case Study

All gear sets produce a gear‑mesh frequency equal to the number of teeth multiplied by the shaft speed. Sidebands appear on both sides of the primary gear‑mesh frequency.

Figure 1 displays data from a planetary gearbox in a lumber operation. The key frequency is 37,915.8 CPM, with a harmonic at 75,831.6 CPM. Sidebands surround this frequency, and time‑waveform impacts confirm meshing defects.

In a planetary gear set—sun gear driving three planet gears that mesh with a ring gear—identifying mesh frequencies can be challenging. The spectrum matches the calculated frequencies, and the waveform impact indicates defective gear teeth.

Defects such as pitting and spalling result from contaminated oil. High meshing pressures (up to 300,000 psi) cause sand and dirt to indent metal teeth, leading to wear. After diagnosis, the unit was removed, repaired, and inspected, revealing visible defects on all three planet gears.

Figure 1. Gear Mesh Data

Detecting this issue via vibration analysis prevented catastrophic gear failure. Without analysis, the defect would have progressed, producing metal shavings and a cascading failure. Oil analysis could have similarly identified wear metals.

Corrective actions, such as balancing, can drastically reduce vibration. Figure 2 shows high‑amplitude vibration at the blower’s 1X speed, indicating imbalance. Figure 3 demonstrates the vibration reduction after balancing, dropping below alarm thresholds and extending equipment life.

Figure 2. Vibration Data from a Fan

Figure 3. Vibration Trend Data After Balancing

Beyond detection, predictive maintenance aims to eliminate recurrence by identifying root causes and implementing preventive measures.

Figure 4 illustrates a bearing fault—an outer‑race defect—identified by sidebands around the fault frequency and amplitude modulation in the time waveform. The software’s bearing database (over 10,000 fault frequencies) labels these frequencies automatically.

Figure 4. Vibration Data from a Bad Bearing

Vibration analysis also identifies resonance risks when operating speeds approach natural frequencies. An impact test, shown in Figure 5, identifies the natural frequency of a structure. Operating within 20 % of 7,313.1 CPM would create resonance, amplifying vibration by up to 20×.

Figure 5. Data Identifying the Natural Frequency of a Structure

Infrared Thermography Case Study

Infrared thermography is widely adopted for its straightforward detection of overheating. Certified interpretation training is recommended to maximize diagnostic accuracy.

Figure 6 highlights a motor starter with a loose “B” terminal connection. The maximum temperature in the hotspot reaches 172.8 °F. Loose connections generate excessive heat, potentially causing a single‑phase failure and premature motor shutdown.

Figure 6. Infrared Data of Motor Starter, Taken by the Author

Figure 7 provides a visual reference to aid technicians in locating the fault.

Figure 7. Image of Problem Area

Infrared thermography’s applications expand beyond low‑voltage systems. Figure 8 shows a high‑voltage line jack at 160.2 °F—more than twice ambient—indicating a loose connection that, if left unchecked, could halt plant operations and cost millions.

Figure 8. Infrared Data of a Loose Connection

Combined with other PdM tools, infrared thermography delivers substantial cost savings by preventing premature failures.

Oil Analysis

Figure 9 displays ISO contaminant levels of 22/21/17, far exceeding typical standards (e.g., 16/14/11). Each numerical increment doubles contaminant concentration, meaning this level is 64 times dirtier than the standard.

Figure 9. Oil Analysis Data

Oil analysis reliably detects contaminants arising from ingress or internal wear. Elevated levels accelerate wear and reduce equipment life. Mitigation includes high‑efficiency filtration (3‑µm, 200 β ratio) and strict leak prevention.

Motor Current Analysis Case Study

Motor current analysis predicts insulation breakdown, allowing preemptive action. When paired with infrared or vibration data, it provides a comprehensive view of electrical and mechanical health.

Figure 10 compares two readings of a humidifier recirculation fan motor: baseline (Sept 7 2005) and follow‑up (July 27 2006). The increase in resistance imbalance (% Res. Imbalance) signals emerging insulation failure, warranting motor removal and reconditioning.

Figure 10. Data Taken by the Author

Motor current analysis also detects air‑gap anomalies, which can cause rotor‑stator rubbing even when other parameters appear normal. Addressing these issues prevents catastrophic motor failure.

Implementing multiple PdM technologies—vibration, infrared, oil, and motor current—provides overlapping insights that dramatically enhance maintenance reliability and reduce downtime costs.

Gary Fore, CMRP
I & E Reliability Specialist
Eagle Rock Energy

About the author:
Gary Fore, CMRP, is an I&E reliability specialist at Eagle Rock Energy. With 22 years in the energy and building products sectors, he focuses on reliability engineering and condition monitoring. His credentials include Certified Maintenance & Reliability Professional, Category III vibration analyst, Level II infrared thermographer, Certified Lubrication Specialist, and Level I machine lubricant analyst.