New Efficiency Standards for Wall Warts in the US

The common household wall wart is now under stricter regulation from the US Government. We can all testify to the waste heat produced by many cheap wall warts. Simply pick one at random in your house, and hold it; it will almost certainly be warm. This regulation hopes to save $300 million in wasted electricity, and reap the benefits, ecologically, of burning that much less fuel.

original
The old standard.

We don’t know what this means practically for the consumer. Will your AliExpress wall warts be turned away at the shore now? Will this increase the cost of the devices? Will it make them less safe? More safe? It’s always hard to see where new regulation will go. Also, could it help us get revenge on that knock-off laptop adapter we bought that go hot it melted a section of carpet?

However, it does look like most warts will go from a mandated 50-ish percent efficiency to 85% and up. This is a pretty big change, and some hold-out manufacturers are going to have to switch gears to newer circuit designs if they want to keep up. We’re also interested to hear the thoughts of those of you outside of the US. Is the US finally catching up, or is this something new?

Gatling Gun Shoots Arrows Out of Coke Bottles

[JoergSprave] has done it again. His latest, most ridiculous weapon? A Gatling gun that fires crossbow bolts, using compressed air inside coke bottles — and an electric screwdriver.

For those of you not aware, [Joerg] is our favorite eccentric German maker, a purveyor of slingshots and all things ridiculous and weaponised. He runs the SlingShot Channel on YouTube, and has graced us with things like a slingshot cannon (firing 220lb balls!), a machete slingshot for the upcoming zombie apocalypse, and more.

Each coke bottle has a quick release pneumatic air valve, with a wooden lever attached to it to make opening the valve easier and quicker. The coke bottles are pressurized separately using an air compressor, but can also be filled using a bicycle pump — he got his hands on a pump capable of putting out 300 PSI! Word of safety though — you really don’t want to use coke bottles as pressure vessels — but [Joerge] is crazy so we’ll let it slide. Continue reading “Gatling Gun Shoots Arrows Out of Coke Bottles”

Frickin’ Amazing Clock

Wwood_clock_05e’ve featured a lot of clock builds, but this one, as the title suggests, is frickin’ amazing. Talented art student [Kango Suzuki] built this Wooden Mechanical Clock (Google translation from Japanese) as a project while on his way to major in product design. There’s a better translation at this link. And be sure to check out the video of it in motion below the break.

[Kango]’s design brief was to do something that is “easy for humans to do, but difficult for machines”. Writing longhand fits the bill, although building the machine wasn’t easy for a human either — he needed six months just to plan the project.

The clock writes time in hours and minutes on a magnetic board. After each minute, the escapement mechanism sets in motion almost 400 wooden cogs, gears and cams. The board is tilted first to erase the old numbers, and then the new numbers are written using four stylii.

The clock doesn’t have any micro controllers, Arduinos, servos or any other electronics. The whole mechanism is powered via gravity using a set of four weights. [Kango] says his biggest challenge was getting the mechanism to write the numbers simultaneously. While he managed the geometry right, the cumulative distortion and flex in the hundreds of wooden parts caused the numbers to be distorted until he tuned around the error.

Continue reading “Frickin’ Amazing Clock”

Embed with Elliot: Audio Playback with Direct Digital Synthesis

Direct-digital synthesis (DDS) is a sample-playback technique that is useful for adding a little bit of audio to your projects without additional hardware. Want your robot to say ouch when it bumps into a wall? Or to play a flute solo? Of course, you could just buy a cheap WAV playback shield or module and write all of the samples to an SD card. Then you wouldn’t have to know anything about how microcontrollers can produce pitched audio, and could just skip the rest of this column and get on with your life.

Harmonic distortion down ~45db on an Arduino
~45db signal to noise ratio from an Arduino

But that’s not the way we roll. We’re going to embed the audio data in the code, and play it back with absolutely minimal additional hardware. And we’ll also gain control of the process. If you want to play your samples faster or slower, or add a tremolo effect, you’re going to want to take things into your own hands. We’re going to show you how to take a single sample of data and play it back at any pitch you’d like. DDS, oversimplified, is a way to make these modifications in pitch possible even though you’re using a fixed-frequency clock.

The same techniques used here can turn your microcontroller into a cheap and cheerful function generator that’s good for under a hundred kilohertz using PWM, and much faster with a better analog output. Hackaday’s own [Bil Herd] has a nice video post about the hardware side of digital signal generation that makes a great companion to this one if you’d like to go that route. But we’ll be focusing here on audio, because it’s easier, hands-on, and fun.

Continue reading “Embed with Elliot: Audio Playback with Direct Digital Synthesis”

Swarm of Robot Boats Coming To An Ocean Near You Soon

Planning a hostile takeover of your local swimming pool? This might help: [Dr Anders Lyhne Christensen] sent us a note about his work at the BioMachines Lab of the Institute of Telecommunications in Portugal. They have been building a swarm of robot boats to experiment with autonomous swarms, with some excellent results.

In an autonomous swarm, each robot makes its own decisions and talks to its neighbors, and the combined behavior of the swarm produces an overall behavior, like ants in a nest. They’ve created swarms that can autonomously navigate, patrol an area or monitor the temperature in an area and return to base to report the results. In an excellent video, [Anders] outlines how they used computational evolution to create these behaviors, randomly mutating a neural net to find the best approach, which is then sent to the real boats.

Perhaps coolest of all: the whole project is open source, with the brains of each boat running on a Raspberry Pi, and a CNC milled foam hull with 3D printed component mounts. Each boat costs about 300 Euro (about $340), but you could reduce the cost a bit by salvaging components and once the less-expensive Pi Zero becomes obtainable. This project will no doubt be useful for many an evil genius who is sick of being splashed by the toughs at the local pool: a swarm of killer robots surrounding them would be an excellent way to keep them at bay.

Continue reading “Swarm of Robot Boats Coming To An Ocean Near You Soon”

Cover Your Glass: A Lesson in Design Trades

Penn and Teller once had a show about “What is the best?” Engineers know that’s not a complete question. Think about a car. What makes the “best” car? It depends on why you want a car. For a race car driver, it might be that speed is the most important factor. A mom might value safety. Someone who commutes four hours a day might like a car that’s comfortable. A teenager wants something affordable.

If you think about it, though, it is even more complicated than that. For example, just about everyone wants a car that is safe. Reliability is pretty important, too. So the reality is, most people want a car that has multiple attributes. Worse still, they sometimes conflict; making one better will make some other ones worse. Mom wants a safe car, but not one that takes half a day to drive to the corner market. Nor does she want to pay a half million dollars for a safe car.

To the Moon

The more complex your system, the more considerations you have to deal with, and the more they affect each other. Tough design trades are what drive the most creative moments in engineering. For example, consider the Lunar Excursion Module (LEM) that carried astronauts from lunar orbit to the moon’s surface. There had never been anything quite like it, and engineers at Grumman had many challenges getting it to a working state.

lemThe model on the left is what people thought the LEM might look like in 1963. You might notice the four relatively large windows. Earlier artist’s renditions had even more glass, looking almost like a helicopter’s cockpit with intrepid astronauts sitting in front of high-tech instrument panels. The original concept vehicle had about 24 square feet of glass.

There are at least two problems with this picture. First, astronauts in space suits need a lot of room to sit down. The seats are also heavy, and every gram of mass on a spacecraft costs a hundred grams in fuel to get to the moon. The other problem is the glass. To hold the air pressure in and provide enough structure, you’d need very thick glass. And glass is surprisingly heavy. Besides that, glass admits a lot of solar radiation.

So the engineers kept shrinking the windows, but this required the seats to get closer to the window and tilt differently so that the astronauts could see out. But if the seats get too close to these smaller windows, it gets harder to maneuver into them while wearing a bulky 1960’s space suit.

There are quite a few design trades going here. The astronauts had to see to land. Remember that video technology wasn’t what it is today, and neither was electronic reliability. So while today you might put no windows in and rely on some redundant cameras, that wasn’t a reasonable option in those days. Some of the other trades involved weight, maintaining a pressurized environment, keeping the astronauts from bouncing around inside the vehicle, and managing radiation exposure.

apollo_lemAs the designed windows got smaller (in the end, they’d wind up with about 3 square feet of glass, down from 24), someone realized that in near-zero G, maybe the astronauts didn’t need to sit at all. If they stood up, they could all but press their noses to the glass and get excellent visibility. It took a little work to ensure they’d be safe standing during the landing, but it all worked out and the final LEM (see right) used the small windows and standing astronauts.

The net result was 90 pounds of weight savings, and a wider cone of vision for landing than most helicopters had at the time. By the way, it is hard to get scale from these pictures, but if you ever see a LEM in person, you’ll probably find it is larger than you think. The claustrophobic CM (command module) was much smaller for three astronauts, but it had different own design trades.

Making a Trade

It turns out that it’s just hard to make a decision with dozens of different factors, even when it isn’t an engineering problem. That’s why business schools teach operations research and multi-criteria decision making. There are several methods that attempt to convert a subjective gut feel approach into a rational mathematical approach.

I’m always suspicious of these processes because they all depend on the humans assigning values in the first place. If you aren’t paying attention, these methods make it look like the decision process is purely scientific. But as the old computer proverb says: Garbage in, garbage out. The fact that you guess at the input values to the algorithm mean that the output is a guess too.

Regardless, if you keep that in mind and try to be fair, some of these methods can be a useful way to organize your thinking. Just remember, you can usually game the numbers to get any answer you want out of these tools. Let’s take one for a spin.

cellSuppose you want to buy a cell phone. There are lots of choices, so you write down the criteria to make the decision. For example (in no particular order): price, weight, battery life, screen size, network type, front camera, rear camera, and storage. Of course, the assumption is that you’ll buy one phone, unlike the cab driver on the right who, apparently, couldn’t make up his mind.

Your list might be different, of course. One difficulty here is making sure these items are actually comparable. For example, CPU speed isn’t on my list. A phone with two brand X cores running at 1 GHz might be slower than a phone with four brand Y cores running at 900 MHz (or vice versa). So selecting on cores or clock speed probably doesn’t mean much unless all the choices have the same kind of CPU.

Working the List

Once you have your list, you need to assign weights to each one. Some criteria will be so important that they must be met, or a candidate is out. These are gating criteria. For example, I might need a phone that takes a GSM card, so any phones that have a network type of CDMA are out no matter what other positive attributes they might have.

Some gates are more conditional. It isn’t uncommon to have a budget. So phones with prices over $400 might be off the table. The other criteria get weights. You can do this in different ways, but the most common method sets weights so that they all add up to 1. Here’s how my table might look on a first pass:

Criterion Weight Hackaphone Makeaphone Orange jPhone Notes
Price 0.15 Must be < $500; less is better
Weight 0.1 Lighter is better
Battery 0.25 Rate against tested run time
Screen 0.2 Larger is better
Network N/A Must be GSM
Front Cam 0.1 More MP better
Rear Cam 0.1 More MP better
Storage 0.1 More is better

It is important to realize that the ratings for each phone (where the dashes are in the table above) aren’t the actual values. They are a relative rating (usually on a 1 to 10 scale). So the price for a $400 phone isn’t 400. It depends on how good the price is relative to the other alternatives. So if the Hackaphone is $400 and the other two phones are $495, you might assign a nine to the Hackaphone (since you wish it were cheaper) and five to the others. On the other hand, if the other two phones were $200, the Hackaphone might get a 2.

You could try to do this mathematically by determining the percentage of the budget that is left over and scaling it so the minimum score is 1. For example:

Int(10*(1-price/budget))+1  or    Int(10*(1-400/500))+1 = 3

That would leave the $495 phones rated at 1. You could also have computed the percent of the budget and assigned a negative weight. However, it isn’t always possible to mathematically scale things into numerical grades. For example, the reliability of a vendor is going to have to be a subjective number.

Once you fill in the grid with the scores, you multiply each entry by the row weight and then add up the columns. The highest score wins. Keep in mind, though, that since this is somewhat subjective, that a score of 78 and 79 might be a tie even though technically 79 is the winner.

Gaming the System

You can probably see how you could manipulate the system. If you wanted to be sure to get an iPhone, you could make FaceTime a gating criterion. Maybe it really is necessary, of course, but it could be that Skype or Google Hangouts would meet your needs just as well. Conversely, I could exclude the iPhone if I made it mandatory to have a micro USB charging port.

Even without gating criteria, it is easy to weight the scores to favor our gut-feeling choice, even if subconsciously. If I know my favorite phone has a high-resolution rear camera, and I weight that very heavily, it increases the odds my favorite camera will win. Unless your primary task is to take great pictures, that probably leads to a bad result. Again, garbage in, garbage out.

Still, if you need to pick between a bunch of transistors, a slew of op amps, or a raft of wireless boards, going through the above process at least organizes your thoughts and forces you to consider what is most important. Just don’t fall into the trap of thinking that it is infallible.

Back to the Moon

lunarThe U.S. space program in the 1960s was nothing short of amazing. The U.S. didn’t even launch a satellite until 1958. Alan Sheppard did a suborbital flight in 1961, and John Glenn did a few orbits in 1962. By 1969, two men walked on the surface of the moon. That was a lot of engineering in the space of about ten years. A lot of what they did, we might today consider hacks.

I’ve heard the stories about the LEM design for many years, but I found the best reference to them in a paper published by [Robert Smythe] at Grumman. There are quite a few lessons you can pick up from reading about what it took to get from nothing to a moon walk in ten years. You can find that and more in [David Mindell’s] Digital Apollo book, which is a great read. Even if you don’t want to read the book, [Mindell’s] sources are interesting reading. Another good source is NASA’s history pages.

The more you read about cases like the LEM, the more apparent it is that engineering is both a science and an art. Structured methods can help you think about a problem. But sometimes getting the best design takes a leap of creativity that you can’t encapsulate in a table of numbers or a math equation. You can use tools to make sure you cover all your bases or to help define the problem. You might need math or testing to prove out that crazy design idea (just like the LEM engineers tested the safety of the standing position). But the crazy–and often best–ideas don’t fall out of a process. They come from creative inspiration.

Cell phone taxi photo by Wesley Fryer (C BY-SA 2.0)

Using Photogrammetry To Design 3D Printed Parts

[Stefan] is building a fixed wing drone, and with that comes the need for special mounts and adapters for a GoPro. The usual way of creating an adapter is pulling out a ruler, caliper, measuring everything, making a 3D model, and sending it off to a 3D printer. Instead of doing things the usual way, [Stefan] is using photogrammetric 3D reconstruction to build a camera adapter that fits perfectly in his plane and holds a camera securely.

ScanPhotogrammetry requires taking a few dozen pictures with a camera, using software to turn these 2D images into a 3D model, and building the new part from that model. The software [Stefan] is using is Pix4D, a piece of software that is coincidentally used to create large-scale 3D models from drone footage.

With the 2D images turned into a 3D model, [Stefan] imported the .obj file into MeshLab where the model could be cropped, smoothed, and the file size reduced. From there, creating the adapter was as simple as a little bit of OpenSCAD and sending the adapter model off to a 3D printer.

Just last week we saw photogrammetry used in another 3D object scanner. The results from both of these projects show real promise for modeling, especially with objects that are difficult to measure by hand.