Shirt Printing With Freezer Paper

June 24, 2015 by Rich Bremer 15 Comments

There’s a pretty good chance that you’ve wanted to add a graphic or design to a t-shirt some time in your life. There are certainly ways to do it but most of us don’t have silk screening equipment or a steady enough hand to have the end product look cool. Lucky for us, [UrbanThreads] has put together a stenciling tutorial for personalizing garments. The process is easy and inexpensive. The results are good, although it can be time-consuming if the pattern is intricate.

To get started, a black and white graphic is printed on a sheet of paper. The design is then taped to a sheet of the secret ingredient: freezer paper. The two sheets are then placed on a table with the freezer paper up. Since the freezer paper is semi transparent, the printed out design shows through. It’s now time to use an exacto knife and trace the design while cutting through the freezer paper. The two sheets are then removed from each other and the freezer paper is put wax-side-down on the garment and ironed into place. The wax melts and acts as a temporary adhesive to hold the stencil down. At this point, fabric paint can be sprayed or dabbed on with a brush (avoid brushing back and forth as it may lift the stencil). Once the paint is applied, the stencil is removed and the paint is allowed to dry. According to [UrbanThreads] the freezer paper doesn’t leave any wax or residue on the garment.

For more garment modding, check out t-shirt bleaching or get ambitious with this DIY screen printing setup.

Machine Metal With Electricity: An EDM Attachment For 3D Printers

June 24, 2015 by Adam Fabio 54 Comments

[SuperUnknown] has revealed a secret project he’s been working on. He’s cooked up an EDM attachment for 3D printers, or any CNC machine for that matter. Electrical Discharge Machining (EDM) is a method of using sparks to machine metal. EDM isn’t a new technology, in fact commercial machines have been around since the 1960’s. If you’ve ever had an arc scar up your multimeter probes, you’ve unwittingly done a bit of EDM.

The theory behind EDM is simple: High voltage between the tool and workpiece causes sparks to jump between them. Each spark erodes the workpiece (and the tool). Big EDM machines perform their magic in a liquid which acts as both a dielectric and a flushing medium. This liquid can be anything from deionzed tap water to specially formulated oil. [SuperUnknown] is using good old-fashioned tap water.

As you can imagine, a single spark won’t erode much metal. EDM machines fire tens of thousands of times per second. The exact frequencies, voltages, and currents are secrets the machine manufacturers keep close to their chests. [SuperUnknown] is zeroing in on 65 volts at 2 amps, running at 35 kHz. He’s made some great progress, gouging into hardened files, removing broken taps from brass, and even eroding the impression of a coin in steel.

While we’d love to say this is a free open source project, [superUnknown] needs to pay the bills. He’s going with crowdsourced funding. No, not another Kickstarter. This project is taking a different route. The videos of the machine will be uploaded to YouTube and visible to [superUnknown’s] Patreon supporters. They will also be available for rent using YouTube’s new rental system. [SuperUnknown] has pledged to figure out a way to make the content available for starving college students and others with limited incomes.

Based upon his previous adventures with lil’ screwy, his homemade 100 ton press, and various other projects on the Arduino verses Evil YouTube channel, we think [superUnkown] has a pretty good chance of making home EDM work. Click past the break to see two videos of the 3D printer EDM toolhead in action. We should mention that [SuperUnknown] is rather colorful with his dialogue, so make sure you’re using headphones if you’re at work.

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Inceptionism: Mind Blown By What Neural Nets Think They See

June 24, 2015 by Will Sweatman 72 Comments

Dr. Robert Hecht-Nielsen, inventor of one of the first neurocomputers, defines a neural network as:

“…a computing system made up of a number of simple, highly interconnected processing elements, which process information by their dynamic state response to external inputs.”

These ‘processing elements’ are generally arranged in layers – where you have an input layer, an output layer and a bunch of layers in between. Google has been doing a lot of research with neural networks for image processing. They start with a network 10 to 30 layers thick. One at a time, millions of training images are fed into the network. After a little tweaking, the output layer spits out what they want – an identification of what’s in a picture.

The layers have a hierarchical structure. The input layer will recognize simple line segments. The next layer might recognize basic shapes. The one after that might recognize simple objects, such as a wheel. The final layer will recognize whole structures, like a car for instance. As you climb the hierarchy, you transition from fast changing low level patterns to slow changing high level patterns. If this sounds familiar, we’ve talked out about it before.

Now, none of this is new and exciting. We all know what neural networks are and do. What is going to blow your mind, however, is a simple question Google asked, and the resulting answer. To better understand the process, they wanted to know what was going on in the inner layers. They feed the network a picture of a truck, and out comes the word “truck”. But they didn’t know exactly how the network came to its conclusion. To answer this question, they showed the network an image, and then extracted what the network was seeing at different layers in the hierarchy. Sort of like putting a serial.print in your code to see what it’s doing.

They then took the results and had the network enhance what it thought it detected. Lower levels would enhance low level features, such as lines and basic shapes. The higher levels would enhance actual structures, such as faces and trees. This technique gives them the level of abstraction for different layers in the hierarchy and reveals its primitive understanding of the image. They call this process inceptionism.

Be sure to check out the gallery of images produced by the process. Some have called the images dream like, hallucinogenic and even disturbing. Does this process reveal the inner workings of our mind? After all, our brains are indeed neural networks. Has Google unlocked the mind’s creative process? Or is this just a neat way to make computer generated abstract art.

So here comes the big question: Is it the computer chosing these end-product photos or a google engineer pawing through thousands (or orders of magnitude more) to find the ones we will all drool over?

Learn 40 Years Of Mech Prototyping At Lightspeed

June 24, 2015 by George Graves 33 Comments

So, what are you doing for the next five and a half hours? If you’re as busy as we are, you might have to digest this amazing 18 part series of videos over the course of a week or so, but we can almost guarantee you’ll learn a lot. It’s a speedrun through the best collection of Mechanical Engineering knowledge we’ve every come across.

In this epic Youtube video series [Dan Gelbart] shares his knowledge of 40 years of prototyping mechanical designs in a way we’ve never seen before. Not only does he show you how to build things, but he gives away a life time of “tips and tricks” that only a veteran builder would know. There are so many little gems of wisdom in this video series, it’s hard to know where to start with our description. He covers all the usual topics: everything from materials, adhesives, coatings, and such. But the real value of this series is all the little trinkets of information he shares along the way.

Don’t be intimated by some of the tools he’s using – chances are there is a DIY version of the piece of equipment out there, and often you can find a hackerspace or enthusiast in the area who will help you out with their gear. We think this video series should be a must watch for any engineering student or hacker. We made a video playlist for you so you can start watching the videos after the break.

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Crawlspace Warehouse Includes Midget Forklift

June 24, 2015 by James Hobson 32 Comments

Meet [Cliff Stoll], producer and entrepreneur-extraordinaire of the ACME Klein Bottles. Years back he helped a friend program a glass oven to get the right temperature profiles for glass blowing. When asked how he wanted to get paid for his help, he asked if they could blow a Klein bottle — and so they did.

Excited at the prospect of his creation, he showed it around to some friends, and was surprised to find out that people wanted to buy it! The one he created took 3 days of sweat and tears to build, so he wasn’t about to start manufacturing them himself. Instead, he decided to call around to some glass manufacturers and see how much he could get Klein bottles made for… That’s when he discovered the power of buying in large quantities.

So what do you do with over 1000 Klein bottles? You build a mini-warehouse in your crawlspace — that’s what.

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Hackaday Prize Entry: Multispectral Imaging Based On LandSat 7

June 23, 2015 by Brian Benchoff 14 Comments

The Landsat series of earth observing satellites is one of the most successful space programs in history. Millions of images of the Earth have been captured by Landsat satellites, and those images have been put to use for fields as divers as agriculture, forestry, cartography, and geology. This is only possible because of the science equipment on these satellites. These cameras capture a half-dozen or so spectra in red, green, blue, and a few bands of infrared to tell farmers when to plant, give governments an idea of where to send resources, and provide scientists the data they need.

There is a problem with satellite-based observation; you can’t take a picture of the same plot of land every day. Satellites are constrained by Newton, and if you want frequently updated, multispectral images of a plot of land, a UAV is the way to go.

[SouthMade]’s entry for the Hackaday Prize, uSenseCam, does just that. When this open source multispectral camera array is strapped to a UAV, it will be able to take pictures of a plot of land at wavelengths from 400nm to 950nm. Since it’s on a UAV and not hundreds of miles above our heads, the spacial resolution is vastly improved. Where the best Landsat images have a resolution of 15m/pixel, these cameras can get right down to ground level.

Like just about every project involving imaging, the [SouthMade] team is relying on off-the-shelf camera modules designed for cell phones. Right now they’re working on an enclosure that will allow multiple cameras to be ganged together and have custom filters installed.

While the project itself is just a few cameras in a custom enclosure, it does address a pressing issue. We already have UAVs and the equipment to autonomously monitor fields and forests. We’re working on the legality of it, too. We don’t have the tools that would allow these flying robots to do the useful things we would expect, and hopefully this project is a step in the right direction.

The 2015 Hackaday Prize is sponsored by:

Pneumatic Multiplexer

June 23, 2015 by Anool Mahidharia 17 Comments

This is a pretty cool project [Sebastian Morales] is working on – a 3D printed Pneumatic Multiplexer. Large interactive installations, kinetic art and many other applications require large numbers of actuators to be controlled. For these type of projects to work, a large number of actuators equals higher resolution and that allows the viewer to be captivated by the piece.

The larger the system becomes, the more complex it becomes to control all of those actuators. [Sebestian] wanted to move a large number of components with a relatively low number of inputs. He thought of creating a mechanical equivalent of the familiar electronic X-Y matrix that can control large quantities of outputs using only a few inputs – in a more descriptive form, Outputs=(Inputs/2)^2.

He looked at chemical reactions that change liquids in to gases, but that seemed pretty complicated. Refrigerants used in air conditioning looked promising, but their handling and safety aspects looked challenging.

Eventually, he decided to look at using “air logic“. Air logic uses pneumatic devices to create relays, limit switches, AND gates, NAND gates, OR gates, amplifiers, equivalent to electrical circuits. Electrical energy is replaced with compressed air. His plan was to build a multiplexer whose elements would open only if the combination of pressure between both lines was the right one. As in electronics, NAND logic is easy to implement. A moving element creates a seal and only allows air out if the bottom line was low and the top line was high.

He had access to a high resolution, resin based 3D printer which allowed him to create fully air-tight systems. He started with prototyping a small 4×4 matrix to test out his design, and had to work through 6 to 7 iterations before he could get it to work. The next step was to create a larger matrix of 100 elements controlled by 20 inputs (10×10 matrix). He created Omnifarious – a kinetic sculpture demonstrating the concept of shapeshifting objects. The Omnifarious is a hexecontahedron which would be able to transform its surface to render different geometries via 59 balloons on its surface. Below, you can check the videos of his progress building the various prototypes and another video showing the Omnifarious sculpture.

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