XXXI International Mineral Processing Congress 2024 Proceedings Page 3735 (3759 of 3836)

3892 XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3
The Q-values show large differences initially. Over the
life of the liner, the differences in Q diminish and converge.
From the DEM, it is possible to isolate and identify the spe-
cific dynamic phenomena responsible for this behaviour:
wear.
THE WEAR SENSOR
The wear sensor system, as outlined in Figure 4, consists of
a detection system fixed the mill. The data is collected by an
edge panel. After some processing, the edge panel forwards
the data to the cloud where the full analysis is completed,
producing the full Q-values. From this Q, the wear state of
the screw can be quantified. The system has been released
by Metso as VertiSense ™.
TRIALS AND RESULTS
The system has been installed at several locations. The
selected mills are of various sizes, with different duties. The
results of one of the trials are presented in Figure 5. In this
case, the life of the liners was approximately 25 weeks. At
the end of that period, new liners were installed during a
brief shutdown.
When compared to the simulation results in Figure 4, a
strong correlation is observed, as illustrated in Figure 6. The
correlation coefficient between the measured and DEM
results is 0.86, indicating a high degree of correlation.
Therefore, the measurement system can determine the
Q-values of the Vertimill.
DISCUSSION
The strong relationship between the measurement and
DEM Q-values provides the ability to construct a system
which can associate the sensor measurements with screw
wear. VertiSense ™ as a Vertimill screw wear sensor works.
Due to the strong relationship between the measure-
ments and some of the dynamics within the mill, it may be
possible to use the measurements to tune the DEM simula-
tion, increasing the accuracy of the model. This coupling
between DEM and measurements is to be further explored.
Finally, the Q-value is found to be sensitive to the
charge level. There is potential for it to be used as an indica-
tion of the charge level in the mill.
Detection
System
Edge Control
Panel Analytics
Figure 4. VertiSense™ architecture
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0 500 1000 1500 2000 2500 3000 3500 4000
Time (h)
Figure 5. Vertimill 1250 measured trial Q-values
Q

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3892 XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3
The Q-values show large differences initially. Over the
life of the liner, the differences in Q diminish and converge.
From the DEM, it is possible to isolate and identify the spe-
cific dynamic phenomena responsible for this behaviour:
wear.
THE WEAR SENSOR
The wear sensor system, as outlined in Figure 4, consists of
a detection system fixed the mill. The data is collected by an
edge panel. After some processing, the edge panel forwards
the data to the cloud where the full analysis is completed,
producing the full Q-values. From this Q, the wear state of
the screw can be quantified. The system has been released
by Metso as VertiSense ™.
TRIALS AND RESULTS
The system has been installed at several locations. The
selected mills are of various sizes, with different duties. The
results of one of the trials are presented in Figure 5. In this
case, the life of the liners was approximately 25 weeks. At
the end of that period, new liners were installed during a
brief shutdown.
When compared to the simulation results in Figure 4, a
strong correlation is observed, as illustrated in Figure 6. The
correlation coefficient between the measured and DEM
results is 0.86, indicating a high degree of correlation.
Therefore, the measurement system can determine the
Q-values of the Vertimill.
DISCUSSION
The strong relationship between the measurement and
DEM Q-values provides the ability to construct a system
which can associate the sensor measurements with screw
wear. VertiSense ™ as a Vertimill screw wear sensor works.
Due to the strong relationship between the measure-
ments and some of the dynamics within the mill, it may be
possible to use the measurements to tune the DEM simula-
tion, increasing the accuracy of the model. This coupling
between DEM and measurements is to be further explored.
Finally, the Q-value is found to be sensitive to the
charge level. There is potential for it to be used as an indica-
tion of the charge level in the mill.
Detection
System
Edge Control
Panel Analytics
Figure 4. VertiSense™ architecture
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0 500 1000 1500 2000 2500 3000 3500 4000
Time (h)
Figure 5. Vertimill 1250 measured trial Q-values
Q

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XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3 3891
mills (Qiu et al 2001). Two decades later, a much more
sophisticated DEM model for Vertimill screw liner wear
was developed (Qiu et al 2024). This model can simulate
the Vertimill liner wear process, capturing the wear charac-
teristics (see Figure 3) and delivering physics related data
including power draw, media grinding energy, and colli-
sional energy.
Figure 4 shows additional DEM results for the
Vertimill. The quantity Q is a synthetic derived physical
quantity. Significant effort was necessary to identify this
quantity its definition is undisclosed and proprietary.
Figure 2. DEM model of the Vertimill screw—actual (R) and simulated (L)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
7 9 11 13 15 17 19 21 23 25
Time
Figure 3. Vertimill DEM Q-value results
Q

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XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3 3893
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 0.2 0.4 0.6 0.8 1
Simulation Q
Figure 6. Comparison between simulation and experimental Q-values
CONCLUSION
In summary, VertiSense ™ is a patented (pending) wear sen-
sor system useful in monitoring the wear state of the screw
in a Vertimill. It is easy to use, easy to install and easy to
maintain. It works without adding any sensors within the
mill chamber. Additionally, the strong relationship between
the measurements and the dynamics within the mill may
allow for the tuning of the DEM simulation to increase its
accuracy. Finally, the Q-values recorded by the VertiSense ™
could potentially be used as an indication of the charge
level in the mill.
REFERENCES
Qiu, X. 2016. DEM simulations in mining and min-
eral processing. In the 7th International Conference
on Discrete Element Methods. August, 2016, Dalian,
China.
Qiu, X., Potapov A., Song M., Nordell L. 2001 Prediction
of wear of mill lifters using discrete element method. In
SAG 2001. January, Vancouver, B.C., Canada.
Qiu, X., and Alkac, D. 2024. Prediction of Vertimill liner
wear by using discrete element method. In XXXI IMPC-
International Mineral Processing Congress. Washington
DC, USA.
Experi
Q

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