High-end Headphones Fixed With High-end CNC Machine

Warranty? We don’t need no stinking warranty! We’re hackers, and if you have access to a multi-million dollar CNC machine and 3D CAM software, you mill your own headphone replacement parts rather than accept a free handout from a manufacturer.

The headphones in question, Grado SR325s, are hand-built, high-end audiophile headphones, but [Huibert van Egmond] found that the gimbal holding the cups to the headband were loosening and falling out. He replicated the design of the original gimbal in CAM, generated the numeric code, and let his enormous Bridgeport milling machine loose on a big block of aluminum. The part was drilled and tapped on a small knee-mill, cut free from the backing material on a lathe, and bead-blasted to remove milling marks. A quick coat of spray paint – we’d have preferred powder coating or anodization – and the part was ready to go back on the headphones.

Sure, it’s overkill, but when you’ve got the tools, why not? And even a DIY CNC router could probably turn out a part like this – a lot slower, to be sure, but it’s still plausible.

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Weather-aware Shoe Rack Helps You Get Ready For The Day

If you’re anything like us, your complete shoe collection consists of a pair of work boots and a pair of ratty sneakers that need to wait until the next household haz-mat day to be retired. But some people have a thing for shoes, and knowing which pair is suitable for the weather on any given day is such a bother. And that’s the rationale behind this Raspberry Pi-driven weather-enabled shoe rack.

The rack itself is [zealen]’s first woodworking project, and for a serious shoeaholic it’s probably too small by an order of magnitude. But for proof of principle it does just fine. The rack holds six pairs, each with an LED to light it up. A PIR sensor on the top triggers the Raspberry Pi to light up a particular pair based on the weather, which we assume is scraped off the web somehow. [zealen] admits that the fit and finish leave a bit to be desired, but for a first Rasp Pi project, it’s pretty accomplished. There’s plenty of room for improvement, of course – RFID tags in the shoes to allow them to be placed anywhere in the rack springs to mind.

[via r/raspberry_pi]

Kinect And Raspberry Pi Add Focus Pulling To DSLR

Prosumer DSLRs have been a boon to the democratization of digital media. Gear that once commanded professional prices is now available to those on more modest budgets. Not only has this unleashed a torrent of online content, it has also started a wave of camera hacks and accessories, like this automatic focus puller based on a Kinect and a Raspberry Pi.

For [Tom Piessens], the Canon EOS 5D has been a solid platform but suffers from a problem. The narrow depth of field possible with DSLRs makes it difficult to maintain focus on subjects that are moving relative to the camera, making follow-focus scenes like this classic hard to reproduce. Aiming for a better system than the stock autofocus, [Tom] grafted a Kinect sensor and a stepper motor actuator to a Raspberry Pi, and used the Kinect’s depth map to drive the focus ring. Parts are laser-cut, including a nice enclosure for the Pi and display that makes the whole thing reasonably portable. The video below shows the focus remaining locked on a selected region of interest. It seems like movement along only one axis is allowed; we’d love to see this system expanded to follow a designated object no matter where it moves in the frame.

If you’re in need of a follow-focus rig but don’t have a geared lens, check out these 3D-printed lens gears. They’d be a great complement to this backwoods focus-puller.

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Shop-built Inspection Camera Lends Optical Help On A Budget

As your builds get smaller and your eyes get older, you might appreciate a little optical assistance around the shop. Stereo microscopes and inspection cameras are great additions to your bench, but often command a steep price. So this DIY PCB inspection microscope might be just the thing if you’re looking to roll your own and save a few bucks.

It’s not fancy, and it’s not particularly complex, but [Saulius]’ build does the job, mainly because he thought the requirements through before starting the build. MDF is used for the stand because it’s dimensionally stable, easy to work, and heavy, which tends to stabilize motion and dampen vibration. The camera itself is an off-the-shelf USB unit with a CS mount that allows a wide range of lenses to be fitted. A $20 eBay macro slider allows for fine positioning, and a ring light stolen from a stereo microscope provides shadow-free lighting.

We’d say the most obvious area for improvement would be a linkage on the arm to keep the plane of the lens parallel to the bench, but even as it is this looks like a solid build with a lot of utility – especially for hackers looking to age in place at the bench.

Arduino Versus Logic: The Coil Gun War Continues

Looks like another shot has been fired in the simmering Coil Gun Control War. This time, [Great Scott] is taken to the discrete woodshed with a simplified and improved control circuit using a single CMOS chip and a few transistors. Where will it end? Won’t somebody think of the children?

The latest salvo is in response to [GreatScott]’s attempt to control a DIY coil gun with discrete logic, which in turn was a response to comments that he took the easy way out and used an Arduino in the original build. [Great Scott]’s second build was intended to justify the original design choice, and seemed to do a good job of explaining how much easier and better the build was with a microcontroller. Case closed, right?

Nope. Embedded designer [fede.tft] wasn’t sure the design was even close to optimized, so he got to work — on his vacation, no less!’ He trimmed the component count down to a single CMOS chip (a quad Schmitt trigger NAND), a couple of switching transistors, the MOSFETs that drive the coils, and a few passives. The NANDs are set up as flip-flops that are triggered and reset by the projectile sensors, which are implemented as hardwired AND gates. The total component count is actually less than the support components on the original Arduino build, and [fede.tft] goes so far as to offer ideas for an alternative that does away with the switching transistors.

Even though [fede.tft] admits that [GreatScott] has him beat since he actually built both his circuits, hats off to him for showing us what can likely be accomplished with just a few components. We’d like to see someone implement this design, and see just how simple it can get.

Fine Business, Good Buddy: Amateur Radio For Truckers

Summer is the season for family road trips here in the US, and my family took to the open road in a big way this year. We pulled off a cross-country relocation, from Connecticut to Idaho. Five days on the road means a lot of pit stops, and we got to see a lot of truck stops and consequently, a lot of long-haul truckers. I got to thinking about their unique lifestyle and tried to imagine myself doing that job. I wondered what I’d do hour after long hour, alone in the cab of my truck. I figured that I’d probably just end up listening to a lot of audio books, but then I realized that there’s a perfect hobby for the road — ham radio. So I decided to see how ham radio is used by truckers, and mull over how a truck driver version of me might practice The World’s Best Hobby.

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Rainy Day Fun By Calculating Pi

If you need a truly random event generator, just wait till your next rainstorm. Whether any given spot on the ground is hit by a drop at a particular time is anyone’s guess, and such randomness is key to this simple rig that estimates the value of pi using raindrop sensors.

You may recall [AlphaPhoenix]’s recent electroshock Settlers of Catan expeditor. The idea with this less shocking build is to estimate the value of pi using the ratio of the area of a square sensor to a circular one. Simple piezo transducers serve as impact sensors that feed an Arduino and count the relative number of raindrops hitting the sensors. In the first video below, we see that as more data accumulates, the Arduino’s estimate of pi eventually converges on the well-known 3.14159 value. The second video has details of the math behind the method, plus a discussion of the real-world problems that cropped up during testing — turns out that waterproofing and grounding were both key to noise-free data from the sensor pads.

In the end, [AlphaPhoenix] isn’t proving anything new, but we like the method here and can see applications for it. What about using such sensors to detect individual popcorn kernels popping to demonstrate the Gaussian distribution? We also can’t help but think of other ways to measure raindrops; how about strain gauges that weigh the rainwater as it accumulates differentially in square and circular containers? Share your ideas in the comments below.

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