What Do You Have in Your Walls?

Alex describes how to find out, using only the sound card in your Linux computer and some wire loops.

A stud sensor can be purchased for as little as $10.00 (US), so why would anyone try to use their Linux computer to look inside walls for power cables, nails, rebar, studs or anything else?

The CanDetect Project came into existence as a side effect of working on a more difficult problem, one where $10.00 of equipment wasn't going to get the job done. Short for Corroding Aircraft Non Destructive Evaluation using software Tools and an Eddy Current Tester, CanDetect aims to provide AMTs (aviation maintenance technicians) with an inexpensive means of performing corrosion inspections on aircrafts. CanDetect seeks to eliminate the expense of specialized computers, external amplifiers, modulators and power supplies, yet still allows an AMT to find tiny defects in metals buried under paint and even under other metals.

Our approach consists of software that can run on any Linux-supported platform and an inspection probe designed to be plugged directly in to the connectors for /dev/dsp—the character device corresponding to the sound card. An application-specific bootable CD-ROM image was developed for the Embedded Linux Journal's NIC contest. If you have a NIC and/or plan to inspect an aircraft, the SourceForge site (candetect.sourceforge.net) has more details. For how to find what is in your walls, read on.

Important Warning: The simple home improvement device described in this article is not approved for use in aviation. Do not use this device in aviation.

The Probe

In earthquake-prone areas, such as California, construction using bricks would be unsafe. Instead, a strong yet lightweight frame consisting of wood or aluminum vertical beams (with approximately 40cm spacing) is covered by a thin, flat layer of particle board, plaster or similar material with enough strength to support only itself. During an earthquake, such a wall would push adjacent furniture over, unless the top of each item has been securely fastened to the wall. When attaching furniture or cabinets to framed walls, it is important to align the screws with the stronger internal structure that can bear a load. Walls also contain pipes and electrical wiring, and it's best to avoid them (obviously) when driving long screws through the wall.

Figure 1. Inductive coil pair, optimized for 10KHz and 2cm depth.

Figure 2. Construction details for the probe shown in Figure 1.

The probe shown in Figure 1 was built by my colleague, Brian Whitecotton. His work is much more photogenic than mine. The probe consists of two coils, whose centers are 2.4" apart, glued to a piece of wood, as shown in Figure 2. Each coil has a diameter of 2.2" and 80 turns of insulated wire. The coils are soldered in series, such that the current rotates in opposite directions, between the left and right signal-out wires. The midpoint between the coils is connected to the mono microphone input. The grounds of the output and input are connected together, as shown in Figure 3. That design has resistance of 6.2 and inductance of 0.8mH.

Figure 3. Schematic of the electrical connections for the probe shown in Figure 1.

When building the probe it is important to verify that the electrical connections are the same and that the two coils are as identical as you can manage. Don't use any other metal in the construction, no matter how tempting, because this probe is designed to detect any metal in nearby walls. By the way, this probe is useless for NDE (nondestructive evaluation) on aircraft.

Wall Signals

Non-physicist Linux users are sometimes intimidated by the physics of these concepts, but don't let that stop you from trying out this project. If nothing else in this section makes sense, know that point sources, such as nails, tend to give rounded signals and line sources, such as power cables, tend to give much more pointy signals.

Figure 4. Prostar notebook 1KHz, linear scan of an invisible dry wall nail.

As it scans across a wall to find invisible nails, the software reports a positive signal when the nail is inside the circle of one coil or a negative signal when the nail is inside the circle of the other coil. This is shown in Figure 4. When trying to examine a large wall area, the coils can travel next to each other so that the sign of the signal indicates which coil encountered a nail. When trying to determine the exact position of a nail, the coils travel along the same path so that the central symmetry with no signal will indicate the location to within a few millimeters.

Figure 5. Prostar notebook 1KHz, linear scan of an invisible 110V> power cable.

Power cables, as shown in Figure 5, or metal structural components obviously will have much larger signals. The shape of the signal distinguishes a point (such as a nail head) from a line (such as a wire). A point has almost the same signal when it's anywhere within the circle of the coil, so the plot has a flattened peak. A line has a signal that varies with the length of the line that is inside the circle, reaching a maximum when it is the diameter. Therefore, the plot has a more pointed peak.

Although a cheap stud sensor can find objects, you must buy a more sophisticated unit if you want more than that basic location. In addition, a cheap sensor cannot distinguish between a water pipe, a structural beam and a power cable.

Figure 6. The phase of the signal suggests what type of metal each object is. Iron and steel are highest, copper and aluminum are lowest, brass and the like are in the middle. Around 1KHz, the phases are clearly separated into three groups.

Figure 7. The signal size suggests how large each object is. Aluminum gives a relatively small signal compared to steel.

More expensive and capable sensors compress their detection results into simple displays. Our software-based sensor can benefit from the better display and adjust the measurement to identify classes of objects. Once an object has been found somewhere inside the wall, the phase of the signal, as shown in Figure 6, indicates what the material is. The size of the signal suggests how big the object is, as shown in Figure 7. The way these two vary with frequency can be used to recognize the shape of the object.