By: Reggie Fett, Motor Circuit Analyst
Industry: Corn Milling Fault Zone: Mechanical
Motor: Toshiba Voltage: 460
Horsepower: 150 Speed: 1785
Motor: Toshiba Voltage: 460
Horsepower: 150 Speed: 1785
Synopsis
The coupling between a motor and its load is prone to problems due to wear and the application. For example, consider the following:
• Belt or direct drive misalignment
• Belt or insert wear
• Belt tension issues (usually resulting in bearing failure)
• Sheave wear
It is true that the most accurate PdM technology for coupling fault detection is vibration analysis. Online Motor Circuit Analysis (MCA) and Infrared (IR) analysis will normally detect severe or late-stage faults; however, this has a lot to do with scheduling and frequency. Utilization of the demodulation spectrum in the online (energized) motor testing software can be a valuable tool for locating mechanical defects with belt, chain, and direct drive applications, as you will see in the following example.
During routine online (energized) MCA data collection of a belt driven application, mechanical anomalies with the belts were identified. Peaks at one times and two times belt running speed were seen in the demodulation spectrum(Figure 1). At one times belt running speed, the focus is on belt and sheave alignment, while at two times belt running speed, the focus is on belt wear.
• Belt or direct drive misalignment
• Belt or insert wear
• Belt tension issues (usually resulting in bearing failure)
• Sheave wear
It is true that the most accurate PdM technology for coupling fault detection is vibration analysis. Online Motor Circuit Analysis (MCA) and Infrared (IR) analysis will normally detect severe or late-stage faults; however, this has a lot to do with scheduling and frequency. Utilization of the demodulation spectrum in the online (energized) motor testing software can be a valuable tool for locating mechanical defects with belt, chain, and direct drive applications, as you will see in the following example.
During routine online (energized) MCA data collection of a belt driven application, mechanical anomalies with the belts were identified. Peaks at one times and two times belt running speed were seen in the demodulation spectrum(Figure 1). At one times belt running speed, the focus is on belt and sheave alignment, while at two times belt running speed, the focus is on belt wear.
Summary of Action
As you can see in Figure 1, the peak at one times belt running speed is near 1.6 decibels. The peak at two times belt running speed is much lower, below 1 decibel. Upon investigating other previously collected test data (vibration and IR thermography), it was identified that this defect was either not present when the previous data was collected or it was not identified at that point. A work order was written for a mechanic to inspect the belts and check for proper alignment.
When the inspection and alignment check were performed, it was determined that the alignment was off and the belts were worn. After performing precision alignment and replacing the belts, the test data collected showed that the peaks in the demodulation spectrum were greatly decreased (Figure 2).
When the inspection and alignment check were performed, it was determined that the alignment was off and the belts were worn. After performing precision alignment and replacing the belts, the test data collected showed that the peaks in the demodulation spectrum were greatly decreased (Figure 2).
Supporting Data
- Figure 1 – Demodulation Spectrum Prior to Repair
- Figure 2 – Demodulation Spectrum Post Repair
Conclusion
When performing online (energized) MCA test data collection on a routine basis, it is extremely beneficial to analyze the demodulation spectrum provided within the motor testing software. Demodulation removes the effect of line frequency (60 Hertz) so a cleaner signature comes out of the noisy spectrum captured by the current analyzer. A cleaned up spectrum is more easily interpreted by the analyst, which allows for remote detection of defects commonly found with vibration analysis in such components as bearings, gears, belt, and chains. This analysis will enable the identification of mechanical defects such as the one described within this case study.
