In a mining plant, internal installation of sensors in the gearboxes of an ore slurry agitator – large equipment critical to the operation – was carried out. Because they were on the inside part, the sensors were enclosed, but this did not prevent automated collection of temperature and vibration data via the Gateway.
The external part of the asset is away from the energy source of the fault, experiencing energy damping. Therefore, installation in this external location would not be recommended. The layout of the mechanical construction of the gearbox is not conducive to capturing the energy of the problem (fault) due to the bronze gear and the screw and gear drive. In case of failure, the asset has an impact on the production process for a long period, due to its location, spare parts, and difficulty to maintain.
The data collected clearly highlighted the gear problem. The reduction of the asset’s gearbox is by screw shaft and gear. It has the following characteristics: input rotation 600 (10Hz), output 32.1 (0.53Hz), reduction factor 18.1, and power 156HP. The screw shaft has 3 inputs, and the bronze gear has 53 teeth. It also has 2 bearings on the input shaft, tapered rollers, and the largest bearing on the gearbox output, which is a special design.
By analyzing all the data available on the DynaPredict Platform, the client’s team was able to clearly visualize the gearing frequencies. This way, they planned accordingly to avoid interruptions in the activity of the asset.
On the platform, the linear and circular waveforms indicate an error in the transmission of force and motion in the component, mainly highlighted by the different amplitudes in the waveform. Thus, in the circular waveform, one can see exactly the number of teeth of the bronze gear (53).
With the platform, it was possible to clearly identify and visualize the gear defect. The applied envelope shows rotation harmonics, an indication of backlash. The origin is the output shaft. This causes a mismatch of tooth contact (one shorter, one longer).
Meanwhile, the envelope waveform below shows, in addition to the symptoms of looseness, a rubbing in the output bearing.
We observed the beats due to the harmonics of the gear frequency in the graphs available on the DynaDetect platform. This asset is now being monitored by the client so that the intervention can take place in a planned manner.
So, even with the sensor rotating next to the part and being covered in oil, the platform’s graphs still showed the problem clearly. This only happens due to the predictability of the fault identification provided by our solution, together with the good analysis work of the client’s predictive maintenance team.
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