Aside from Strayos using AI to detect rock mass features, there is also a manual annotation tool that can be used to mark such features on a highwall. Our Rock Joint and Seam annotation tool is found on the annotation tool bar. 

When selected, you will be brought into the 3D view, where you will manually draw an annotation line along the rock joint or seam. This will then appear as an annotation that can be moved or edited easily. Visually, the 3D lines intruding the face are all a constant length, however they follow the surface of the highwall. See, how the vectors are interpolated below the Burden Profile.   

If the 3D view is adjusted to show the "inside" of the highwall where we can also see a bore hole, you can now see where the feature may intersect the bore hole.  This feature is also seen in the burden report, where it will show the Dip angle and Strike direction to the corresponding holes that lay behind. This is assuming the feature intersects the borehole.  

Lastly, this annotation tool can be downloaded in the following formats show below:

Below is a breakdown on how the vectors are formed and interpolated when drawn by the user: 

When a joint annotation is finished being drawn it sticks to the surface of the model by finding the closest point on the model along a small interval. These are the sample points.

The algorithm is based on the idea that the seam in the rock is a continuous surface that touches every sample point generated in the previous step. We then construct the simplest possible set of lines that describe that surface. These are called cross seam lines (every point is connected to it’s closest possible neighbors without crossing over each other).

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These data points from the last step are fed to a best fit line algorithm, giving us a resulting vector.

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Accuracy is proportional to the “thickness” of the data. Annotations that go around bends or over very rough surfaces will have the deepest set of data points for each sample point. Annotations over flat surfaces will only have a few data points that are very clustered.

It’s also important to draw annotations as accurate to the seam as possible. It can continuously be adjusted after the fact as well.