Measuring air flow in an HVAC duct can be a tricky business. Paddle wheel and turbine flow meters introduce not only resistance but maintenance issue due to accumulated dust and debris. Being able to measure ducted airflow cheaply and non-intrusively, like with this ultrasonic flow meter, could be a big deal for DIY projects and the trades in general.
The principle behind the sensor [ItMightBeWorse] is working on is nothing new. He discovered a paper from 2015 that describes the method that measures the change in time-of-flight of an ultrasonic pulse across a moving stream of air in a duct. It’s another one of those “Why didn’t I think of that?” things that makes perfect sense in theory, but takes some engineering to turn into a functional sensor. [ItMightBeWorse] is using readily available HC-SR04 sensor boards and has already done a proof-of-concept build. He’s getting real numbers back and getting close to a sensor that will go into an HVAC automation project. The video below shows his progress to date and hints at a follow-up video with more results soon.
Here’s wishing [ItMightBeWorse] the best of luck with his build. But if things go sideways, he might look to our post-mortem of a failed magnetic flow meter for inspiration.
Continue reading “Measuring Air Flow with Ultrasonic Sensors”
Pour yourself a nice hot cup of tea, because [iliasam]’s latest work on a laser rangefinder (in Russian, translated here) is a long and interesting read. The shorter version is that he got his hands on a broken laser security scanner, nearly completely reverse-engineered it, got it working again, put it on a Roomba that was able to map out his apartment, and then re-designed it to become a tripod-mounted, full-room 3D scanner. Wow.
The scanner in question has a spinning mirror and a laser time-of-flight ranger, and is designed to shut down machinery when people enter a “no-go” region. As built, it returns ranges along a horizontal plane — it’s a 2D scanner. The conversion to a 3D scanner meant adding another axis, and to do this with sufficient precision required flipping the rig on its side, salvaging the fantastic bearings from a VHS machine, and driving it all with the surprisingly common A4988 stepper driver and an Arduino. A program on a PC reads in the data, and the stepper moves another 0.36 degrees. The results speak for themselves.
This isn’t [iliasam]’s first laser-rangefinder project, naturally. We’ve previously featured his homemade parallax-based ranger for use on a mobile robot, which is equally impressive. What amazes us most about these builds is the near-professional quality of the results pulled off on a shoestring budget.
Continue reading “Amazing 3D-Scanner Teardown and Rebuild”
Every robotics project out there, it seems, needs a way to detect if it’s smashing into a wall repeatedly, acting like the brainless automaton it actually is. The Roomba has wall sensors, just about every robot kit has some way of detecting obstacles its running into, and for ‘wall-following robots’, detecting objects is all they do.
While the earliest of these robots used a piece of wire and a metal contact to act like a switch for these object detectors, ultrasonic sensors – the kind you can buy on eBay for a few bucks – have replaced this clever wire spring switch. Now there’s a new sensor for the same job – the VL6180 – and it measures the speed of light.
The sensors that are used for object and collision detection now use either ultrasonic or infrared light. They’re susceptible to noise, and if you’re doing anything automated, you really don’t want rogue measurements. A time of flight sensor clocks out photons and records how long it takes them to return at 299,792,458 meters per second. It’s less sensitive to noise, and if you can believe this SparkFun demo of this sensor, extremely accurate
This is not the first Time of Flight distance sensor on the market; earlier this week we saw a project use a sensor called the TeraRanger One. This sensor costs €150.00. The VL6180 sensor costs about $6 in quantity one from the usual suspects, and breakout boards with the proper level converters and regulators can be found for about $25. More expensive sensors have a greater range, naturally; the VL6180 is limited to somewhere between 10cm (on paper) and 25cm (in practice). But this is cheap, and it measures the time of flight of pulses of light. That’s just cool.
Here is a two-part Navy training film from 1953 that describes the inner workings of mechanical fire control computers. It covers seven mechanisms: shafts, gears, cams, differentials, component solvers, integrators, and multipliers, and does so in the well-executed fashion typical of the era.
Fire control systems depend on many factors that occur simultaneously, not the least of which are own ship’s speed and course, distance to a target, bearing, the target’s speed and course if not stationary, initial shell velocity, and wind speed and direction.
The mechanisms are introduced with a rack and pinion demonstration in two dimensions. Principally speaking, a shaft carries a value based on revolutions. From this, a system can be geared at different ratios.
Cams take this idea further, transferring a regular motion such as rotation to an irregular motion. They do so using a working surface as input and a follower as output. We are shown how cams change rotary motion to linear motion. While the simplest example is limited to a single revolution, additional revolutions can be obtained by extending the working surface. This is usually done with a ball in a groove.
Continue reading “Retrotechtacular: Fire Control Computers in Navy Ships”
[Matthias] recently published a paper he worked on, in which he details how his group managed to reconstruct a hidden scene using a wall as a mirror in a reasonably priced manner. A modified time-of-flight camera (PMD CamBoard Nano) was used to precisely know when short bursts of light were coming back to its sensor. In the picture shown above the blue represents the camera’s field of view. The green box is the 1.5m*1.5m*2.0m scene of interest and we’re quite sure you already know that the source of illumination, a laser, is shown in red.
As you can guess, the main challenge in this experience was to figure out where the three-times reflected light hitting camera was coming from. As the laser needed to be synchronized with the camera’s exposure cycle it is very interesting to note that part of the challenge was to crack the latter open to sniff the correct signals. Illumination conditions have limited impact on their achieved tolerance of +-15cm.