Arduino And FPGA Done Differently

FPGA guru [Max Maxfield] recently took a look at the XLR8 (pronounced accelerate) board from a company called Alorium. On the surface, it looks like another Arduino UNO clone. But instead of a CPU, it contains an Intel MAX10 FPGA that runs a softcore AVR processor. Of course, that’s only part of the story. If the board was just a mock Arduino using an FPGA, that’s not very interesting for practical purposes. However, by incorporating accelerator blocks or XBs, you can add FPGA modules to the soft CPU. [Max] shows an example that you can see in the video below where an FPGA block controls servos more easily than a standard Arduino. There’s also a version that looks like an Arduino Nano, but can clock much faster as well as use the XBs.

In addition to prebuilt XBs, there is a workflow to build your own if you are familiar with working with FPGAs. The products aren’t exactly new, but we enjoyed [Max’s] take on the product. We also appreciated the simple code examples showing exactly how you would convert a program to use the accelerated functions. Continue reading “Arduino And FPGA Done Differently”

Phasors In LTSpice

[Ted] recently demonstrated the analysis of an RL circuit using a piece of paper, Octave, and LTSpice. If you prefer, the Octave code should work fine in MATLAB, as well. If you are looking to get serious about electronic theory this is a reasonably simple case and is a good chance to get a workout with some of the tools.

We like the approach because too often it is easy to just use the computer and not pick up the understanding that you get when working through a problem by hand. You do need to understand complex numbers, but, overall, the math isn’t too hairy.

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Science Officer…Scan For Elephants!

If you watch many espionage or terrorism movies set in the present day, there’s usually a scene where some government employee enhances a satellite image to show a clear picture of the main villain’s face. Do modern spy satellites have that kind of resolution? We don’t know, and if we did we couldn’t tell you anyway. But we do know that even with unclassified resolution, scientists are using satellite imagery and machine learning to count things like elephant populations.

When you think about it, it is a hard problem to count wildlife populations in their habitat. First, if you go in person you disturb the target animals. Even a drone is probably going to upset timid wildlife. Then there is the problem with trying to cover a large area and figuring out if the elephant you see today is the same one as one you saw yesterday. If you guess wrong you will either undercount or overcount.

The Oxford scientists counting elephants used the Worldview-3 satellite. It collects up to 680,000 square kilometers every day. You aren’t disturbing any of the observed creatures, and since each shot covers a huge swath of territory, your problem of double counting all but vanishes.

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Custom Components In LTSpice

If you enjoy simulating circuits, you’ve probably used LTSpice. The program has a lot of powerful features we tend to not use, including the ability to make custom components that are quite complex. To illustrate how it works, [asa pro] builds a potentiometer component that is not only a good illustration but also a useful component.

The component is, of course, just two resistors. However, using parameters, the component gets two values, a total resistance and a percentage. Then the actual resistance values adjust themselves.

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Raspberry Pi Cosmic Ray Detector

[Marco] has a sodium iodide detector that indicates cosmic radiation by scintillation. The material glows when hit by cosmic rays and, traditionally, a photomultiplier tube detects the photos from the detection. After a quick demonstration that you can see in the video below, he built the Cosmic Pi, a CERN project to create a giant distributed cosmic ray detector. The Cosmic Pi uses scintillation, but not from a crystal. It uses a plastic scintillator and silicon photodetectors, so it is much easier to work with than a traditional detector.

Using a four-layer board and some harvested components, the device detects muons. There are two scintillation detectors and muons striking both detectors presumably don’t have a local origin. The instrument has a GPS to get accurate time and position data. There are other sensors onboard, too, to collect data about the conditions of each detected event.

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Raspberry Pi Pico ADC Characterized

[Markomo] didn’t find much useful information about the Raspberry Pi PIco’s analog to digital converter, so he decided to do some tests to characterize it. Lucky for us, he documented the findings and shared them. The results are in a series of blog posts that cover power supply noise, input-referred noise, signal to noise ratio, and distortions.

There are some surprising results. For example, the Pico’s low noise regulator mode appears to produce more noise than having it set for normal operation. There also appears to be a large spike in nonlinearity around certain measurements.

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Photorender Your 3D Models

Of course, you’ll want to take your latest 3D design and print it so you’ll have a physical object. But in some cases, you’d like to have a rendering of it. If you use OpenSCAD, FreeCAD, or most other CAD programs you can get a simple rendering of your object, but what if you want something that looks real? [Teaching Tech] shows how you can use a website, Vectary, to get realistic photo renderings of your 3D models. (Video, embedded below.) The free plan has a few limits, but nothing that should bother most people.

Vectary is sort of like a super version of TinkerCad with a lot of options for realistic modeling and augmented reality. Some of the more advanced features are behind a subscription plan, but for what [Teaching Tech] is showing, you can use the free plan.

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