Over the months of August, September and October last year, Dynamox installed vibration and temperature sensors for continuous and wireless monitoring. During this period, an increase in vibration levels was identified in a bearing housing of a belt conveyor. This component is considered crucial to Iron+ Mining’s efficient production process.
The WEB Platform detected this increase and was responsible for receiving the global data captured by Dynamox’s sensors. The monitoring team was promptly notified of this out-of-range condition via A2 alerts.
These alerts, meanwhile, offer the flexibility of customization, adapting to the specific vibration characteristics of each asset. This allows the maintenance team or operators in charge to be notified automatically when necessary, even by email in cases of A2 (the most ‘serious’ alert). This approach allows preventive measures to be taken promptly in the event of potential problems.
Vibration sensor and Web Platform detection
During the analysis of the vibration spectrum, we identified a change in the acceleration parameter, with the presence of notable harmonics at a frequency of 7.56 Hz. This frequency is characteristic of the bearing outer race (BPFO), considering the rotation of 60 RPM, located in the right bearing housing of the conveyor belt’s return pulley.
In the following image, it is possible to clearly see the frequency identified and its modulation by the rotation, indicating the severity of the problem. These signs strongly suggest the existence of a looseness in the system.
During the analysis and identification of the looseness in one of the asset’s bearings, the team also checked the reports collected over the monitoring months. In this context, it is possible to observe the evolution of the problem, as well as its resolution following the maintenance carried out.
Early identification of the condition, through the Dynamox solution, offered the Iron+ Mining team the opportunity to take measures to avoid potential failures in the asset, as well as optimizing the operational reliability of the equipment. Therefore, an intervention was scheduled, and the bearing was replaced at an appropriate time.
See next how the RMS velocity data decreased after the intervention on the belt conveyor:
Did you like the case study? You can also read “Fault Tree Analysis: how to apply it in your plant“.