Hardware hacking can be extremely multidisciplinary. If you only know bits and bytes, but not solder and electrons, you’re limited in what you can build. The same is true for mechanical design, where the forces of stress and strain suddenly apply to your project and the pile of code and PCBs comes crashing to the ground.
In the first half of his workshop, Naman Pushp walks you through some of the important first concepts in mechanical engineering — how to think about the forces in the world that act on physical objects. And he brings along a great range of home-built Jugaad props that include a gravity-defying tensegrity string sculpture and some fancy origami that help hammer the topics home.
In the second half of the workshop, Naman takes these concepts into computer simulation, and gives us good insight into the way that finite-element analysis simulation packages model these same forces on tiny chunks of your project’s geometry to see if it’ll hold up under real world load. The software he uses isn’t free by any definition — it’s not even cheap unless you have a student license — but it’s nonetheless illuminating to watch him work through the flow of roughly designing an object, putting simulated stresses and strains on it, and interpreting the results. If you’ve never used FEA tools before, or are looking for a compressed introduction to first-semester mechanical engineering, this talk might be right up your alley. Continue reading “Remoticon Video: The Mechanics Of Finite Element Analysis”
When thoughts turn to measuring the degree to which something bends, it’s pretty likely that strain gauges or some kind of encoders on a linkage come to mind. Things could be much simpler in the world of flex measurement, though, if [Fereshteh Shahmiri] and [Paul H. Dietz]’s capacitive multi-bend flex sensor catches on.
This is one of those ideas that seems so obvious that you don’t know why it hasn’t been tried before. The basic idea is to leverage the geometry of layered materials that slip past each other when bent. Think of the way the pages of a hardbound book feather out when you open it, and you’ll get the idea. In the case of the ShArc (“Shift Arc”) sensor, the front and back covers of the book are flexible PCBs with a series of overlapping pads. Between these PCBs are a number of plain polyimide spacer strips. All the strips of the sensor are anchored at one end, and everything is held together with an elastic sleeve. As the ShArc is bent, the positions of the electrodes on the top and bottom layers shift relative to each other, changing the capacitance across them. From the capacitance measurements and the known position of each pad, a microcontroller can easily calculate the bend radius at each point and infer the curvature of the whole strip.
The video below shows how the ShArc works, as well as several applications for the technology. The obvious use as a flex sensor for the human hand is most impressive — it could vastly simplify [Will Cogley]’s biomimetic hand controller — but such sensors could be put to work in any system that bends. And as a bonus, it looks pretty simple to build one at home.
Continue reading “Slipping Sheets Map Multiple Bends In This Ingenious Flex Sensor”
When you saw the picture for this article, did you think of a peacock’s feather? These fibers are not harvested from birds, and in fact, the colors come from transparent rubber. As with peacock feathers, they come from the way light reflects off layers of differing materials, this is known as optical interference, and it is the same effect seen on oil slicks. The benefit to using transparent rubber is that the final product is flexible and when drawn, the interference shifts. In short, they change color when stretched.
Most of the sensors we see and feature are electromechanical, which has the drawback that we cannot read them without some form of interface. Something like a microcontroller, gauge, or a slew of 555 timers. Reading a single strain gauge on a torque wrench is not too tricky, but simultaneously reading a dozen gauges spread across a more complex machine such as a quadcopter will probably require graphing software to generate a heat map. With this innovation it could now be done with an on-board camera in real-time. Couple that with machine learning and perhaps you could launch Skynet. Or build a better copter.
The current proof-of-concept weaves the fibers into next-generation bandages to give an intuitive sense of how tightly a dressing should be applied. For the average first-aid responder, the rule is being able to slide a finger between the fabric and skin. That’s an easy indicator, but it only works after the fact whereas saying that the dressing should be orange while wrapping gives constant feedback.