Sometimes we get complacent and begin to take for granted some truly amazing things that happen all around us every day. Who among us doesn't grumble when, as we turn on the computer, Windows again updates itself? And yet, for all its flaws, it's an amazing system.

So it is, too, with the laser scanning system that Colin Milberg is using to gather and analyze data from which he hopes to derive more rational construction tolerances for building with concrete.

On a recent visit to one of the civil engineering labs at San Diego State University, where Milberg is an assistant professor, I watched his team's green laser zip back and forth across a 10x50-foot erosion table, precisely and methodically gathering data about the surface. That system is fascinating enough, particularly to someone who has worked with a dumpy level and a rod man taking shots every 10 or 20 feet. But that's only the beginning.

The amazing part is watching how the data are rendered into an image. Now, I'm still impressed by 3-D rendering software that lets you spin a wire frame representation of an object so you can look at it from above, below, and every angle in between. Seeing the surface of that erosion bed appear on the screen, bit by bit, as the laser scanned was awe-inspiring.

This image of the concrete wall’s front face has a best-fit plane embedded in it. The standard deviation given in the information window shows how flat the wall is. It is much like an FF number except that lower standard deviations indicate better flatness. The direction of normal (a line drawn perpendicular to the surface) can be compared to the design normal in the x and y directions to determine orientation variation (i.e., the extent to which the wall is skewed relative to the building gridlines.) The z direction of the normal will tell you if the wall is out of plumb. It is zero for this wall, indicated that it's plumb.
Photos: Colin Milberg, Ph.D., San Diego State Univ. This image of the concrete wall’s front face has a best-fit plane embedded in it. The standard deviation given in the information window shows how flat the wall is. It is much like an FF number except that lower standard deviations indicate better flatness. The direction of normal (a line drawn perpendicular to the surface) can be compared to the design normal in the x and y directions to determine orientation variation (i.e., the extent to which the wall is skewed relative to the building gridlines.) The z direction of the normal will tell you if the wall is out of plumb. It is zero for this wall, indicated that it's plumb.

Think about the specifics: this device repeatedly measures distance and location to within a few millimeters—there are 25.4 millimeters per inch—and it does that at the rate of 4000 points per second. But the software is the key to turning that raw data into useful information.

Milberg's team is using a Trimble GX 3-D scanner for this project. As it is with much of the high-tech equipment surrounding us these days, each major scanner manufacturer offers its own software designed specifically to work with its equipment. This machine incorporates what Trimble calls its Vision technology to combine live video on the controller screen with the data being collected from each scanned point. The result is data rendered in a real-world, visual context.

The software interface between the scanner and the notebook computer, to which the data are collected, is Trimble's PointScape. That control unit software “manages point cloud data capture.” It allows you to do such things as frame the area you wish to scan and provides you with onscreen data about the scanned points and the various surfaces they form.

The company's RealWorks Survey software, which also runs on the notebook computer, uses the data from a scan to show a 3-D image on the screen, as well as to work with the embedded information. For example, consider a scanned wall. The program can place a “best-fit plane” within that wall surface and report the mathematical values comparing the as-built and as-designed conditions.

The results are very much like floor flatness measurements. The standard deviation calculated for the points relative to the best-fit plane is the equivalent of an FF number. The FL equivalent is the angular difference between two lines drawn at right angles to the best-fit plane and the actual wall surface. A separate value is calculated for vertical and horizontal directions. The best part of it all is that it all happens automatically and instantaneously. Whoever thought you could get FF and FL numbers for a wall? But like real magic, it's simply the manipulation of real things in the real world.