Overview
Emesent Aura’s Change Detection and Convergence Monitoring solution integrates the rapid data capture capabilities of the Hovermap with Aura's intuitive processing and analysis to help you manage and monitor your excavation projects.
Frequently Asked Questions
How do I view Convergence from outside of the tunnel? (Similar to MC32 in Cloud Compare)
We understand that viewing data outside of the drive can be easier for analysis in some cases. Some customers may be familiar with Cloud Compare’s MC32 workflow creates a single skin by taking an average of all the points and creating a plane. Whereas Aura takes an averaged mesh to a scan with a thickness which means you need to view Convergence from inside the tunnel. If this sort of visualization is required, users can bring the two aligned Aura Convergence monitoring output into Cloud Compare and run MC32.
Are the Hovermap 100, ST, and ST-X all supported?
Yes technically all Hovermaps are supported to use the workflow, though the most accurate Hovermap ST-X product will improve the accuracy of the convergence monitoring result and is therefore the recommended product for this use case.
Why are the original bag files required?
The bag files are required for reference and second scans as the SLAM algorithm is run on the raw data as part of the alignment process.
How close does the user need to roughly align the two scans for the convergence monitoring workflow to be successful?
The Aura alignment algorithm will search for matching features between scans within the Max Distance parameter, defaulting to 0.5m. Ensuring the rough alignment of scans is as close as possible improves the likelihood of a good final alignment.
Does convergence monitoring work with GCP for georeferencing my data?
We understand georeferencing is important as it helps with pattern recognition where some structure is moving in context to another, considering context to the stoping front and for bringing in lithology data. Aura doesn’t support using GCP as part of the Convergence monitoring workflow yet. We are looking to support this in a future release. In the meantime, some customers using this solution are bringing the Aura output into Cloud Compare and using a 4-point method with spray-painted marks to georeference the data.
If I don't use GCP, will a long scan matter if the two scans have drift? Can they still be aligned and be usable for convergence monitoring?
The Aura alignment algorithm will fix the reference scan in place, and align the second scan to the reference scan. This has the benefit of reducing drift in scans aligned for Convergence Monitoring.
What is the impact of noise like clutter, people, and dust in the scan?
False changes will be detected if objects or people are in one scan and not in the other.
What is the expected level of accuracy?
Measurements in a small controlled environment showed an average error of approximately 12mm. Accuracy will vary depending on factors such as the size of the scanned area, features in the scan, speed of the scan, and density of scanned areas.
How will changes in the drive that are unrelated to convergence monitoring impact our solution? For example, the vent bag is inflated on one scan and not on the other, changes on the drive floor, or changes created by vehicles knocking out chunks of the wall.
The alignment of the scans and the resulting distance values may be affected in areas with limited matching features. Small changes such as missing chunks in the wall typically will not largely impact the alignment of the scans.
Can I use non-Hovermap scans for convergence monitoring?
No. Only Hovermap scans are supported.
If two or more scans are merged to capture a longer tunnel, can that merged scan be used for convergence monitoring?
No. Currently, convergence monitoring only supports comparing between two Hovermap scans.