The Art Of Electronics, Third Edition

January 29, 2015 by 81 Comments

For any technical domain, there is usually one book held up above all others as the definitive guide. For anyone learning compilers, it’s the dragon book. For general computer science, it’s the first half of [Knuth]’s The Art of Computer Programming. For anyone beginning their studies of electrons and silicon, it’s [Horowitz & Hill]’s The Art of Electronics. This heady tome has graced workbenches and labs the world over and is the definitive resource for anything electronica. The first edition was published in 1980, and the second edition was published in 1989. Now, finally, the third edition is on its way.

The new edition will be released on April 30, 2015 through Cambridge University Press, Amazon, and Adafruit. In fact, [PT] over at Adafruit first announced the new edition on last night’s Ask An Engineer show. [Ladyada] was actually asked to provide a quote for the cover of the new edition, an incredible honor that she is far too humble about.

The latest edition is about 300 pages longer than the second edition. It is thoroughly revised and updated, but still retains the casual charm of the original. Real copies do not exist yet, and the only critical review we have so far is from [Ladyada]. There will be few surprises or disappointments.

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Fail Of The Week: Electrically Effective Emulators Exceed Enclosure, Enrage Engineer

January 29, 2015 by 20 Comments

After a few years of on and off development, [Steve] from Big Mess ‘o Wires completed work on a floppy disk drive emulator for older Macs such as the Plus. The emu plugs into the DB-19 port on the Mac and acts just like a 3.5″ floppy, using an SD card to store the images. He’s been selling the floppy emus for about the last year, and assembled the first several scores of them himself. At some point, he enlisted a board house to make them, and as of November 2014, he’s had enclosures available in both clear acrylic and brown hardboard.

[Steve] recently ran out of emu stock, so it was time to call up the board house and get some more assembled. After waiting six weeks, they finally showed up. But in spite of [Steve]’s clear and correct instructions, all 100 boards are messed up. One resistor is missing altogether, and they transposed a part between the extension cable adapter board, connecting it directly to the emu main board. But get this: the boards still work electrically. They don’t fit in the housings, however, and the extension cables are useless. After explaining the situation, the board house agreed to cook up a new batch of boards, which [Steve] is waiting patiently to receive.

2013-09-05-Hackaday-Fail-tips-tileFail of the Week is a Hackaday column which runs every Wednesday. Help keep the fun rolling by writing about your past failures and sending us a link to the story — or sending in links to fail write ups you find in your Internet travels.

SPATA: Shaving Seconds And Saving Brainpower Whilst 3D-modeling

January 29, 2015 by 20 Comments

If you’ve spent some late nights CADing your next model for the 3D printer, you might find yourself asking for a third hand: one for the part to-be-modeled, one for the tool to take measurements, and one to punch the numbers into the computer. Alas, medical technology just isn’t there yet. Luckily, [Christian] took a skeptical look at that third hand and managed to design it out of the workflow entirely. He’s developed a proof-of-concept tweak on conventional calipers that saves him time switching between tools while 3D modeling.

His build [PDF] is fairly straightforward: a high-resolution digital servo rests inside the bevel protractor while a motorized potentiometer, accelerometer, and µOLED display form the calipers. With these two augmented devices, [Christian] can do much more than take measurements. First, both tools are bidirectional; not only can they feed measurement data into the computer with the push of at button, both tools can also resize themselves to a dimension in the CAD program, giving the user a physical sense of how large or small their dimensions are. The calipers’ integrated accelerometer also permits the user to perform CAD model orientation adjustments for faster CAD work.

How much more efficient will these two tools make you? [Christian] performs the same modeling task twice: once with conventional calipers and once with his tools. When modeling with his augmented device, he performs a mere 6 context switches, whereas conventional calipers ratchet that number up to 23.

In a later clip, [Christian] demonstrates a design workflow that combines small rotations to the model while the model is sculpted on a tablet. This scenario may operate best for the “if-it-looks-right-it-is-right” sculpting mindset that we’d adopt while modeling with a program like Blender.

Of course, [Christian’s] calipers are just a demonstration model for a proof-of-concept, and the accuracy of these homemade calipers has a few more digits of precision before they can rival their cousin on your workbench. (But why let that stop you from modifying the real thing?) Nevertheless, his augmented workflow brings an elegance to 3D modeling that has a “clockwork-like” resonance of the seasoned musician performing their piece.

[via the Tangible, Embedded, and Embodied Interaction Conference]

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Is That A Tuner In Your Pocket…?

January 29, 2015 by 38 Comments

As a musician, it’s rare to consistently recognize with the naked ear whether or not a single instrument is in tune. There are a number of electronic devices on the market to aid in this, however if you’re leading into an impromptu performance to impress your friends, using one feels about as suave as putting on your dental headgear before bed. When tuning is necessary, why not do so in a fashion that won’t cramp your style?

To help his music-major friends add an element of Bond-like flare to the chore, [dbtayl] designed a chromatic tuner that’s disguised as a pocket watch, pet-named the “pokey”. The form for the custom casing was designed in OpenSCAD and cut from aluminum stock on a home-built CNC mill. Under its bass-clef bedecked cover is the PCB which was laid out in KiCad to fit the watch’s circular cavity, then milled from a piece of copped-clad board. The board contains the NXP Cortex M3 which acts as the tuner’s brain and runs an FFT (Fast Fourier Transform) that uses a microphone to match the dominant pitch it hears to the closest note. Five blue surface-mount LEDs on the side indicate how sharp or flat the note is, with the center being true.

[dbtayl’s] juxtaposition of circuitry in something that is so heavily associated with mechanical function is a clever play on our familiarity. You can see a test video of the trinket in action below:

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Raspberry Pi Learns How To Control A Combustion Engine

January 28, 2015 by 17 Comments

For his PhD at the University of Michigan, [Adam] designed a Raspberry Pi-based system that controls an HCCI engine, a type of engine which combines the merits of both diesel and gasoline engines. These engines exhibit near-chaotic behavior and are very challenging to model, so he developed a machine learning algorithm on a Raspberry Pi that adaptively learns how to control the engine.

[Adam]’s algorithm needs real-time readings of cylinder pressures and the crankshaft angle to run. To measure this data on a Raspberry Pi, [Adam] designed a daughterboard that takes readings from pressure sensors in each cylinder and measures the crankshaft angle with an encoder. The Pi is also equipped with a CAN transceiver that communicates with a low-level engine control unit.

RasPi HCCI Engine Control[Adam]’s algorithm calculates engine control parameters in real-time on the Pi based on the pressure readings and crankshaft position. The control values are sent over CAN to the low-level engine controller. The Pi monitors changes in the engine’s performance with the new values, and makes changes to its control values to optimize the combustion cycle as the engine runs. The Pi also serves up a webpage with graphs of the crankshaft position and cylinder pressure that update in real-time to give some user feedback.

For all the juicy details, take a look at [Adam]’s paper we linked above. For a more visual breakdown, check out the video after the break where [Adam] walks you through his setup and the awesome lab he gets to work in.

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TeaSteeper

Automated Tea Maker

January 28, 2015 by 17 Comments

[Pariprohus] wanted to make an interesting gift for his girlfriend. Knowing how daunting it can be to make your own tea, he decided to build a little robot to help out. His automated tea maker is quite simple, but effective.

The device runs off of an Arduino Nano. The Nano is hooked up to a servo, a piezo speaker, an LED, and a switch. When the switch is turned to the off position, the servo rotates into the “folded” position. This moves the steeping arm into a position that makes the device easier to store and transport.

When the device is turned on to the “ready” position, the arm will extend outward and stay still. This gives you time to attach the tea bag to the arm and place the mug of hot water underneath. Finally the switch can be placed into “brew” mode. In this mode, the bag is lowered into the hot water and held for approximately five minutes. Each minute the bag is raised and lowered to stir the water around.

Once the cycle completes, the Nano plays a musical tune from the piezo speaker to remind you to drink your freshly made tea. All of the parameters including the music can be modified in the Nano’s source code. All of the components are housed in a small wooden box painted white. Check out the video below to see it in action. Continue reading “Automated Tea Maker” →

A Camera With Computer Vision

January 28, 2015 by 25 Comments

Computer vision is a tricky thing to stuff into a small package, but last year’s Hackaday Prize had an especially interesting project make it into the 50 top finalists. The OpenMV is a tiny camera module with a powerful microcontroller that will detect faces, take a time-lapse, record movies, and detect specific markers or colors. Like a lot of the great projects featured in last year’s Hackaday Prize, this one made it to Kickstarter and is, by far, the least expensive computer vision module available today.

[Ibrahim] began this project more than a year ago when he realized simple serial JPEG cameras were ludicrously expensive, and adding even simple machine vision tasks made the price climb even higher. Camera modules that go in low-end cell phones don’t cost that much, and high-power ARM microcontrollers are pretty cheap as well. The OpenMV project started, and now [Ibrahim] has a small board with a camera that runs Python and can be a master or slave to Arduinos or any other microcontroller board.

The design of the OpenMV is extraordinarily clever, able to serve as a simple camera module for a microcontroller project, or something that can do image processing and toggle a few pins according to logic at the same time. If you’ve ever wanted a camera that can track an object and control a pan/tilt servo setup by itself, here you go. It’s a very interesting accessory for robotics platforms, and surely something that could be used in a wide variety of projects.