The first thing I ever built without a kit was a 5 V regulated power supply using the old LM309K. That’s a classic linear regulator like a 7805. While they are simple, they waste a lot of energy as heat, especially if the input voltage goes higher. While there are still applications where linear regulators make sense, they are increasingly being replaced by switching power supplies that are much more efficient. How do switchers work? Well, you buy a switching power supply IC, add an inductor and you are done. Class dismissed. Oh wait… while that might be the best way to do it from a cost perspective, you don’t really learn a lot that way.
In this installment of Circuit VR, we’ll look at a simple buck converter — that is a switching regulator that takes a higher voltage and produces a lower voltage. The first one won’t actually regulate, mind you, but we’ll add that in a future installment. As usual for Circuit VR, we’ll be simulating the designs using LT Spice.
Interestingly, LT Spice is made to design power supplies so it has a lot of Linear Technology parts in its library just for that purpose. However, we aren’t going to use anything more sophisticated than an op amp. For the first pass, we won’t even be using those.
Continue reading “Circuit VR: Simple Buck Converters”
Readers with long memories will remember the days when mice and other similar pointing devices relied upon a hard rubber ball in contact with your desk or other surface, that transmitted any motion to a pair of toothed-wheel rotation sensors. Since the later half of the 1990s though, your rodent has been ever significantly more likely to rely upon an optical sensor taking the form of a small CCD camera connected to motion sensing electronics. These cameras are intriguing components with applications outside pointing devices, as is shown by [FoxIS] who has used one for robot vision.
The robot in question is a skid-steer 4-wheeled toy, to which he has added an ADNS3080 mouse sensor fitted with a lens, an H-bridge motor driver board, and a Wemos D1 Mini single board computer. The D1 serves a web page showing both the image from the ADNS3080 and an interface that allows the robot to be directed over a network connection. A pair of LiPo batteries complete the picture, with voltage monitoring via one of the Wemos analogue pins.
The ADNS3080 is an interesting component and we’d love see more of it. This laser distance sensor or perhaps this car movement tracker should give you some more info. We’ve heard rumors of them being useful for drones. Anyone?
There seems to be a universal truth on the Internet: if you open up a service to the world, eventually somebody will come in and try to mess it up. If you have a comment section, trolls will come in and fill it with pedantic complaints (so we’ve heard anyway, naturally we have no experience with such matters). If you have a service where people can upload files, then it’s a guarantee that something unsavory is eventually going to take up residence on your server.
Unfortunately, that’s exactly what [Christian Haschek] found while developing his open source image hosting platform, PictShare. He was alerted to some unsavory pictures on PictShare, and after he dealt with them he realized these could be the proverbial tip of the iceberg. But there were far too many pictures on the system to check manually. He decided to build a system that could search for NSFW images using a trained neural network.
The nude-sniffing cluster is made up of a trio of Raspberry Pi computers, each with its own Movidius neural compute stick to perform the heavy lifting. [Christian] explains how he installed the compute stick SDK and Yahoo’s open source learning module for identifying questionable images, the aptly named open_nsfw. The system can be scaled up by adding more Pis to the system, and since it’s all ARM processors and compute sticks, it’s energy efficient enough the whole system can run off a 10 watt solar panel.
After opening up the system with a public web interface where users can scan their own images, he offered his system’s services to a large image hosting provider to see what it would find. Shockingly, the system was able to find over 3,000 images that contained suspected child pornography. The appropriate authorities were notified, and [Christian] encourages anyone else looking to search their servers for this kind of content to drop him a line. Truly hacking for good.
This isn’t the first time we’ve seen Intel’s Movidius compute stick in the wild., and of course we’ve seen our fair share of Raspberry Pi clusters. From 750 node monsters down to builds which are far more show than go.