People trying to replicate their favorite items and gadgets from video games is nothing new, and with desktop 3D printing now at affordable prices, we’re seeing more of these types of projects than ever. At the risk of painting with too broad a stroke, most of these projects seem to revolve around weaponry; be it a mystic sword or a cobbled together plasma rifle, it seems most gamers want to hold the same piece of gear in the physical world that they do in the digital one.
But [Jonathan Whalen] walks a different path. When provided with the power to manifest physical objects, he decided to recreate the iconic “Question Block” from the Mario franchise. But not content to just have a big yellow cube sitting idly on his desk, he decided to make it functional. While you probably shouldn’t smash your head into the thing, if you give it a good knock it will launch gold coins into the air. Unfortunately you have to provide the gold coins yourself, at least until we get that whole alchemy thing figured out.
Printing the block itself is straightforward enough. It’s simply a 145 mm yellow cube, with indents on the side to accept the question mark printed in white and glued in. A neat enough piece of decoration perhaps, but not exactly a hack.
The real magic is on the inside. An Arduino Nano and a vibration sensor are used to detect when things start to get rough, which then sets the stepper motor into motion. Through an ingenious printed rack and pinion arrangement, a rubber band is pulled back and then released. When loaded with $1 US gold coins, all you need to do is jostle the cube around to cause a coin to shoot out of the top.
If this project has got you interested in the world of 3D printed props from the world of entertainment, don’t worry, we’ve got you covered.
Continue reading “Beat This Mario Block Like it Owes You Money”
Lots of people set out to build appliance monitors, whether it be for the fridge, the garage door, or the washing machine. Often, it’s nicer not to cut into an appliance to make direct electrical connections, especially when mains power or water is involved. But how else can we know what the appliance is doing?
[Drew Dormann] wanted to smarten up his old washing machine, so designed a system that uses a vibration sensor to monitor appliances. It’s a simple build, pairing the 801s vibration sensor with a Raspberry Pi Zero. Naturally, adapter boards are readily available to make hooking things up easy. Then it’s just a matter of tying it all together with a simple Python script which sends notifications using Twitter & PushBullet.
It’s important to note that this approach isn’t just limited to washing machines – there’s a whole laundry list of home appliances that vibrate enough to be monitored in this way! It’s likely you could even spy on a communal microwave in this way, though you might struggle with WiFi dropouts due to interference. Build it and let us know.
[Drew]’s build is a great example of what you can put together in a few hours with parts off the shelf. For those that consider the Pi Zero overkill for this application, consider this vibration-based laundry monitor based on the ESP8266. Think you can do better? Show us what you’ve got on Hackaday.io!
Every machine has its own way of communicating with its operator. Some send status emails, some illuminate, but most of them vibrate and make noise. If it hums happily, that’s usually a good sign, but if it complains loudly, maintenance is overdue. [Ariel Quezada] wants to make sense of machine vibrations and draw conclusions about their overall mechanical condition from them. With his project, a 3-axis Open Source FFT Spectrum Analyzer he is not only entering the Hackaday Prize 2016 but also the highly contested field of acoustic defect recognition.
For the hardware side of the spectrum analyzer, [Ariel] equipped an Arduino Nano with an ADXL335 accelerometer, which is able to pick up vibrations within a frequency range of 0 to 1600 Hz on the X and Y axis. A film container, equipped with a strong magnet for easy installation, serves as an enclosure for the sensor. The firmware [Ariel] wrote is an efficient piece of code that samples the analog signals from the accelerometer in a free running loop at about 5000 Hz. It streams the digitized waveforms to a host computer over the serial port, where they are captured and stored by a Python script for further processing.
From there, another Python script filters the captured waveform, applies a window function, calculates the Fourier transform and plots the spectrum into a graph. With the analyzer up and running, [Ariel] went on testing the device on a large bearing of an arbitrary rotating machine he had access to. A series of tests that involved adding eccentric weights to the rotating shaft shows that the analyzer already makes it possible to discriminate between different grades of imbalance.