It’s a boat! It’s a hackerspace! It’s a DIY research platform and an art gallery! It’s Boat Lab!
[Andrew Quitmeyer] lead a project in the Philippines that was nominally charged with making an art and technology space. After a few days brainstorming, four groups formed and came up with projects as wide-ranging as a water-jet video screen and a marine biology lab. What did they have in common? They were all going to take place on a floating raft hackerspace in a beautiful body of water in Manila.
This is a really crazy meta-project, and any of the sub-projects would be worth their own blog post. Even more so is the idea itself — building a floating hackerspace is just cool. The write-up on Hackaday.io linked above is pretty comprehensive, and the “Waterspace” book talks a bit more about the overarching process. Boat Lab is a great entry into the Citizen Science phase of the Hackaday Prize 2016.
But we also love the idea of hackerspaces in non-traditional places. The Cairo Hackerspace is working on a van-based space. And now we’ve seen a boat. What other mobile hackerspace solutions are out there? We’d love to hear!
We’ve all made rash and impulsive online purchasing decisions at times. For [Drygol] the moment came when he was alerted to an Atari 1040STe 16-bit home computer with matching monitor at a very advantageous price.
He did have one lucky break, the seller had carefully wrapped everything in shrink-wrap so no fragments had escaped. So carefully applying acetone to stick the ABS together he set to work on assembling his unexpected 3D jigsaw puzzle. The result needed a bit of filler and some sanding, but when coupled with a coat of grey paint started to look very like an ST case that had just left the factory. Adding modern SD card and USB/Ethernet interfaces to the finished computer delivered a rather useful machine as you can see in the video below the break. Continue reading “An Atari ST Rises From The Ashes”→
It’s great to hear from people who say they’re inspired to fix stuff by reading about hacks here on Hackaday. [Michael Lüftenegger] from Salzburg is one of them. About a year back, he snagged a digital horn from eBay that turned out to be dead-er than advertised and he wrote a post about how he fixed it and gave it a second life.
The Casio DH-100 is an electronic MIDI digital wind controller/synthesizer musical instrument. Your breath flows through the instrument, making it feel pretty similar to acoustic wind instruments. [Michael]’s unit had already seen some attempted, but unsuccessful repairs. Nothing that could not be fixed, except that the main pressure sensor was missing. Without the sensor, the instrument was practically useless. The eBay seller wasn’t lying when he described the unit as working with breath mode turned off! Continue reading “Reviving a Dead Zanzithophone”→
Nitinol is a kind of wire that has a memory. If you heat it, it tries to return to the shape it remembers. [Latheman666] recently posted a video (see below) of a Nitinol engine that uses a temperature differential to generate motion.
[Dr. Alfred Johnson] holds a patent on this kind of motor. The concept sounds simple enough. A Nitnol spring shrinks in hot water and expands in cold. The spring is looped over two pulleys. One pulley is geared so it has mechanical advantage over the other one so that there’s a net torque which moves the hot part of the spring towards the cold side, and feeds more cold spring into the hot water. The cold spring then contracts and the entire process starts again.
We haven’t entirely gotten our heads around the gearing, but it seems plausible. On the other hand, this video was posted on April 1. What say you, Hackaday Commenteers?
With more and more previously industrial processes coming online in the home shop, people are finding that getting the information that was previously provided by the manufacturer of a hundred thousand dollar machine for their three hundred dollar Shenzen special is not easy.
A common example is this, a hacker purchased themselves a brand new 3D printer off amazon for a price too good to be true. After a week of tinkering with it, a small fire, and a few replacement parts later, they get it to work. After they’ve burned through, perhaps literally, the few hundred grams of filament that came with the printer at the setting recommended by the manufacturer, they do a small blanket order of the different filaments out there. Now comes the trouble, each printer is a little different and each filament has different properties. Most people find that the second spool of filament they feed into their printer doesn’t work at all. What’s the quickest way to get the right temperature, cooling, and feed settings for your printer configuration?
This isn’t a problem for the expensive machines. Epilog, a manufacturer of laser cutters, provides a grid of settings for each material you’re likely to cut, tuned to the different properties of each model of laser cutter they sell. Same goes for the expensive industrial 3D printers, each (very expensive) spool of material has the setting sitting in a chip in the casing. When the spool is slotted in the machine, it reads the settings and adjusts accordingly. All the work of tuning was done in a lab somewhere and the print is, theoretically, guaranteed.
While we were at the Bay Area Makerfaire 2016, we had a chance to talk to [Gauthier de Valensart] and buy him a beer at the Hackaday Meet-up. [Gauthier] is from Belgium where he is the founder of a start-up with one of those fancy new TLDs: filaments.directory. The goal of filaments.directory is to create a database of 3D printer materials and link that up with a user’s 3D printer settings. The eventual goal being, much like the industrial printers, a user would be able to simply scan a barcode, or wave the spool over an RFID reader to input the needed settings into his slicing software or printer.
This sounded familiar to me, not the least because I had started work on it as an extension for repables.com when that was a larger focus in my life. In fact, I remember, while I was kicking the idea around to people at MRRF, that they kept telling me someone else was working on a similar project. I wanted to introduce [Gauthier] to the person who was working on the project back then. Since I was at a bar full of people in the industry, I sort of helplessly rotated in my spot trying to find someone who might remember. I spied [whosawhatsis], a common attendee of MRRF, and asked him. Okay, that was easy, [whosawhatsis] informed us that is was his project… introduction complete. Goes to show you what a good networking event buying a bunch of nerds beer can be.
The project was called, “Universal Filament Identification System,” and it proposed to, “… eliminate the guess-work,” by, “…developing a method for tagging, tracking, and identifying filament for 3d printing in machine-readable formats…” The project appears to be mostly dead now and its domain is a placeholder. I think it suffered from the standard open source feature creep, but the idea is sound.
Which gets us to the questions. There are a lot of difficulties with creating such a system. The first being the data collection. Who should be responsible for measuring the filaments, the materials for laser cutting, or any other process that needs tuned settings? The ideal track, of course, would be for the manufacturers to hold themselves accountable and report on the settings for their filaments. However, many filament manufacturers rely on the ignorance of users to sell dodgy products, it’s only in the interest of a few top-quality ones to do so. If the users do so, then how will the information provided be vetted? You definitely don’t want someone’s ignorance about a faulty thermistor to encourage you to run PLA at 280C.
More and more difficulties arise. How should the information be transferred, etc. What properties should even be recorded? UFID was going as far as to use a color sensor to keep track of colors between batches from 3D printer manufacturers. In the end it’s about creating standards in a standard-less industry by using crowdsourcing. Either way, take a look at what [Gauthier]’s doing (and send him some feedback), read the backlogs of UFID, think about how annoying it was to get the right settings for a laser cutter the last time you used one, and let us know your thoughts in the comments.
[Fabian Chouteau] built a plotter out of CD-ROM parts. Yawn, you say? Besides being a beautiful physical build, this one has a twist. He wrote the software and firmware for the entire project himself, in Ada.
Ada is currently number two on our list of oddball programming languages that should be useful for embedded programming. It’s vaguely Pascal-y, but with some modern object-oriented twists. It was developed for safety-critical, real-time embedded systems (by the US Department of Defense), and is used in things like airplanes, rockets, and the French TGV trains. If that sounds like overkill for your projects, [Fabian]’s project shows that it’s still very tractable.
In his GitHub, he re-implements the GRBL G-code generator and then writes a GUI front-end for it. In his writeup, he mentions that the firmware and its simulator for the front-end use exactly the same code which is quite a nice trick, and guarantees no (firmware) surprises when moving from the modelled device to the real thing.
Between Tesla Motors’ automobiles and SpaceX’s rockets, Elon Musk’s engineers just have to be getting something right. In part, SpaceX’s success in landing their first stage rockets is due to analysis of telemetry data. You can see some of the data from their launch vehicles on the live videos and there is surely a lot more not shown.
An article in MIT Technology Review provides similar insights in how Tesla came from behind in autonomous vehicle operation by analyzing telemetry from their cars. Since 2014 their Model S received an increasing number of sensors that all report their data over the vehicle’s always-on cellular channel. Sterling Anderson of Tesla reported they get a million miles of data every 10 hours.
The same approach can help us to improve our systems but many believe creating a log of key data is costly in time and resources. If your system is perfect (HA HA!) that would be a valid assessment. All too often such data becomes priceless if analysis explains why your drone or robot wanted to go left into a building instead of right into the open field.