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STRUCTURALLY SOUND
Jason Gillham, Director of Operations, 2G Robotics Inc., provides an experimental comparison of underwater sonar and laser measuring
In underwater inspection, there is a need for sensors that can determine the structure of an asset. The most prevalent technology in this field is sonar. There are, however, physical limitations to the resolution capability of these technologies for understanding small, yet important, features of structures such as cracks and erosion in concrete structures or welds and dents in metallic marine infrastructure. Underwater laser scanners are not affected by the same physical principles as sonar and have the ability to capture details of underwater assets that were previously unobtainable.
Sonar Principles
Active sonar ranging is based on emitting a pulse of sound energy to a target surface and measuring the time taken for an echo to return. Based on the speed of sound in water, the distance to the target surface can be calculated. As sound travels through the water it spreads apart and 3D sonar systems assume that the contact point is in the centre of the beam of sound energy when converting the return to a 3D point. The precision of sonar systems is limited because they must approximate a relatively large footprint area with a single point.
Laser Principles
Laser scanners are widely used in terrestrial applications for high resolution measurements. The 2G Robotics ULS-100 and ULS-500 underwater laser scanner uses a trigonometric approach. The sensor head sends a laser line to the target surface, and an optical sensor captures the return signal. The 3D position of hundreds of points along that laser line are calculated, forming a profile of the target. The energy footprint of a laser beam is far smaller than that of a sonar beam, permitting a much higher measurement resolution. The measurement resolution is multiple orders of magnitude higher, enabling very dense point clouds.
Results
To demonstrate the difference between the capability of sonar and laser for measuring underwater, a cinder block wall was constructed with target features including missing blocks and offset blocks. The wall was scanned with both the 2G Robotics ULS-100 underwater laser scanner and a mechanically scanning 3D sonar using a 2.25Mhz head with an average angular point spacing of one degree. The point cloud data for the two methods has been overlaid, with laser scanner data in red and black, and sonar data in green. The scans generally align well, indicating that both systems are capable of accurately assessing an asset's large-scale structure. However, there is significantly greater detail in the sonar measurements, and the measurement resolution is much better, as shown in Figure 1. The laser system also resolves edges much more precisely than sonar. As Figure 2 illustrates, the hole in the wall is resolved with very good detail using the laser scanner. While it is possible to identify the presence and general location of the hole in the sonar data, it does not provide a precise understanding of the hole's edges and an accurate position and size for the hole cannot be determined. This inaccuracy is due to the size of the sonar system's footprint. A chip in the corner of a block, shown in Figure 3, does not appear at all in the sonar data. By surfacing the laser scanner data a clear understanding of this small but potentially important feature can be achieved.
Conclusions
Sonar and laser technologies have complimentary features. Long-range sonar scans can be used to assess the general structure of an asset, where high levels of detail are not required. If maintenance is necessary, laser scanner data provides a more complete understanding of repair requirements, reducing risk and lowering the cost of deployment. The complete paper describing the experimental comparison between the 3D sonar and ULS-100 Underwater Laser Scanner can be found on the 2G Robotics website.
www.2grobotics.com
Figure 1
Figure 2: Top and Front View of hole in the wall indicating indicating the error potential with sonar measurements compared to laser data
Figure 3: Zoomed in View
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