Neural Network Helps With Radar Pipeline Diagnostics

Diagnosing pipeline problems is important in industry to avoid costly or dangerous failures from cracked, broken, or damaged pipes. [Kutluhan Aktar] has built an system that uses AI to assist in this difficult task.

The core of the system is a MR60BHA1 60 GHz mmWave radar module, which is most typically used for breathing and heartrate detection. Here, it’s repurposed to detect fluctuating vibrations as a sign that a pipeline may be cracked or damaged. It’s paired with an Arduino Nicla Vision module, with the smart camera able to run a neural network model on the captured radar data to flag potential pipe defects and photograph them. The various modules are assembled on a PCB resembling Dragonite, the Dragon/Flying-type Pokemon.

[Kutluhan] walks us through the whole development process, including the creation of a web interface for the system. Of particular interest is the way the neural network was trained on real defect models that [Kutluhan] built using PVC pipe. We’ve looked at industrial pipelines in detail before, too. Video after the break.

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Smart Occupancy Sensor Knows All

In the last few decades, building engineers and architects have made tremendous strides in improving the efficiency of various buildings and the devices that keep them safe and comfortable to live in. The addition of new technology like heat pumps is a major factor, as well as improvements on existing things like insulation methods and building materials. But after the low-hanging fruit is picked, technology like this smart occupancy sensor created by [Sina Moshksar] might be necessary to help drive further efficiency gains.

Known as RoomSense IQ, the small device mounts somewhere within a small room and uses a number of different technologies to keep track of the number of occupants in a room. The primary method is mmWave radar which can sense the presence of a person up to five meters away, but it also includes a PIR sensor to help prevent false positives and distinguish human activity from non-human activity. The device integrates with home automation systems to feed them occupancy data to use to further improve the performance of those types of systems. It’s also designed to be low-cost and easy to install, so it should be relatively straightforward to add a few to any existing system as well.

The project is also documented on this GitHub page, for anyone looking to build a little more data into their home automation system or even augment their home security systems. We imagine that devices like this could be used with great effect paired with a heating device like this, and we’ve also seen some other interesting methods of determining occupancy as well.

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Machining Waveguides For 122 GHz Operation Is Delicate Work

Millimeter-wave Radars used in modern cars for cruise control and collision avoidance are usually designed to work at ranges on the order of 100 meters or so. With some engineering nous, however, experimenters have gotten these devices sending signals over ranges of up to 60 km in some tests. [Machining and Microwaves] decided to see if he could push the boat out even further, and set out machining some waveguide combiner cavities so he could use the radar chips with some very high-performance antennas.

Precision-machined components are required to successfully use these 122 GHz components for long-range transmissions.

The end goal of the project is to produce a 53 dBi antenna for the 122GHz signal put out by the mmWave radar chips commonly found in automotive applications. Working at this frequency requires getting tolerances just so in order to create an antenna that performs well.

Plenty of fine lathe work and cheerful machining banter later, and the precision waveguide is done. It may not look like much to the untrained eye, but much careful design and machining went on to make it both easy to attach to the radar and parabolic antenna system, and to make it perform at a high enough level to hopefully break records set by other enterprising radio experimenters. If that wasn’t all hard enough, though, the final job involved making 24 of these things!

There aren’t a whole lot of microwave antenna-specific machining channels on YouTube, so if you’ve been thirsty for that kind of content, this video is very much for you. If you’re more interested in antennas for lower frequencies, though, you might find some of our other stories to your liking. Video after the break.

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