1024 “Pixel” Sound Camera Treats Eyes to Real-Time Audio

A few years ago, [Artem] learned about ways to focus sound in an issue of Popular Mechanics. If sound can be focused, he reasoned, it could be focused onto a plane of microphones. Get enough microphones, and you have a ‘sound camera’, with each microphone a single pixel.

Movies and TV shows about comic books are now the height of culture, so a device using an array of microphones to produce an image isn’t an interesting demonstration of FFT, signal processing, and high-speed electronic design. It’s a Daredevil camera, and it’s one of the greatest builds we’ve ever seen.

[Artem]’s build log isn’t a step-by-step process on how to make a sound camera. Instead, he went through the entire process of building this array of microphones, and like all amazing builds the first step never works. The first prototype was based on a flatbed scanner camera, simply a flatbed scanner in a lightproof box with a pinhole. The idea was, by scanning a microphone back and forth, using the pinhole as a ‘lens’, [Artem] could detect where a sound was coming from. He pulled out his scanner, a signal generator, and ran the experiment. It didn’t work. The box was not soundproof, the inner chamber should have been anechoic, and even if it worked, this camera would only be able to produce an image or two a minute.

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8×8 microphone array (mics on opposite side) connected to Altera FPGA at the center

The idea sat in the shelf of [Artem]’s mind for a while, and along the way he learned about FFT and how the gigantic Duga over the horizon radar actually worked. Math was the answer, and by using FFT to transform a microphones signals from up-and-down to buckets of frequency and intensity, he could build this camera.

That was the theory, anyway. Practicality has a way of getting in the way, and to build this gigantic sound camera he would need dozens of microphones, dozens of amplifiers, and a controller with enough analog pins, DACs, and processing power to make sense of all of this.

This complexity collapsed when [Artem] realized there was an off-the-shelf part that was a perfect microphone camera pixel. MEMS microphones, like the kind found in smartphones, take analog sound and turn it into a digital signal. Feed this into a fast enough microcontroller, and you can perform FFT on the signal and repeat the same process on the next pixel. This was the answer, and the only thing left to do was to build a board with an array of microphones.

4x4[Artem]’s camera microphone is constructed out of several modules, each of them consisting of an 8×8 array of MEMS microphones, controlled via FPGA. These individual modules can be chained together, and the ‘big build’ is a 32×32 array. After a few problems with manufacturing, the board actually worked. He was recording 64 channels of audio from a single panel. Turning on the FFT visualization and pointing it at a speaker revealed that yes, he had indeed made a sound camera.
The result is a terribly crude movie with blobs of color, but that’s the reality of a camera that only has 32×32 resolution. Right now the sound camera works, the images are crude, and [Artem] has a few ideas of where to go next. A cheap PC is fast enough to record and process all the data, but now it’s an issue of bandwidth; 30 sounds per second is a total of 64 Mbps of data. That’s doable, but it would need another FPGA implementation.

Is this sonic vision? Yes, technically the board works. No, in that the project is stalled, and it’s expensive by any electronic hobbyist standards. Still, it’s one of the best to grace our front page.

[Thanks zakqwy for the tip!]

Blue Ribbon Microphone

Edmund_Lowe_fsa_8b06653If you’ve ever seen an old movie or TV show where there was a radio announcer, you’ve probably seen a ribbon microphone. The RCA 44 (see Edmund Lowe, on right) had exceptional sound quality and are still valued today in certain applications. The name ribbon microphone is because the sound pickup is literally a thin strip of aluminum or other conductive material.

Unlike other common microphones, ribbons pick up high frequencies much better due to the high resonant frequency of the metallic ribbon. This is not only better in general, but it means the ribbon mic has a flatter frequency response even at lower frequencies. Another unique feature is that the microphone is bidirectional, hearing sounds from the front or back equally well. It is possible to build them with other directional patterns, although you rarely see that in practice.

Invention

In the early 1920s, Walter Schottky and Erwin Gerlach developed the ribbon microphone (and, coincidentally, the first ribbon loudspeaker). Harry Olson at RCA developed a ribbon mic that used coils and permanent magnets which led to the RCA Photophone Type PB-31 in 1931. Because of their superior audio response, they were instant hits and Radio City Music Hall started using the PB-31 in 1932. A newer version appeared in 1933, the 44A, which reduced reverberation.

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Audio-coupled Smoke Alarm Interface Sends Texts, Emails

The Internet of Things is getting to be a big business. Google’s Nest brand is part of the trend, and they’re building a product line that fills niches and looks good doing it, including the Nest Protect smoke and CO detector. It’s nice to get texts and emails if your smoke alarm goes off, but if you’d rather not spend $99USD for the privilege, take a look at this $10 DIY smoke alarm interface.

The secret to keeping the cost of [Team SimpleIOThings’] interface at a minimum is leveraging both the dirt-cheap ESP8266 platform and the functionality available on If This Then That. And to keep the circuit as simple and universal as possible, the ESP8266 dev board is interfaced to an existing smoke detector with a simple microphone sensor. From what we can see it’s just a sound level sensor, and that should work fine with the mic close to the smoke detector. But with high noise levels in your house, like those that come with kids and dogs, false alarms might be an issue. In that case, we bet the software could be modified to listen for the Temporal-Three pattern used by most modern smoke detectors. You could probably even add code to send a separate message for a CO detector sounding a Temporal-Four pattern.

Interfacing to a smoke detector is nothing new, as this pre-ESP8266 project proves. But the versatile WiFi SoC makes interfaces like this quick and easy projects.

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Listen to the Rain, Raspberry Pi Style

There’s an old proverb algebra teachers often recite: You have to use what you know to find out what you don’t know. The same could be said about sensors. For example, analog to digital converters use something computers are good at finding (like time) and use it to determine something they aren’t good at finding (like voltage). So how do you detect rainfall? If you are [lowflyerUK], you use the microphone in your web camera and a Raspberry Pi.

The idea was to reduce irrigation usage based on rainfall, so an exact measurement isn’t necessary. The Python code that analyzes the audio input is calibrated with three configuration parameters and attempts to remove wind noise. Even so, it needs to be in a room that gets a lot of noise from rainfall and ambient noise can throw the reading off.

The weather service is never going to adopt this system. Still, it is a great example of taking something you know and using it to get something you don’t know. If you want a more complete weather station, we have a few options for you.

Make a Microphone Out of a Hard Drive

[Rulof Maker] has a penchant for making nifty projects out of old electronics. The one that has caught our eye is  a microphone made from parts of an old hard drive. The drive’s arm and magnet were set aside while  the aluminum base was diagonally cut into two pieces.  One piece was later used to reassemble the hard drive’s magnet and arm onto a wooden platform.

v2_micThe drive’s arm and voice coil actuator are the key parts of this project. It was modified with a metal extension so that a paper cone cut from an audio speaker could be attached, an idea used in microphone projects we’ve previously featured. Copper wire scavenged from the speaker was then soldered to voice coil on the arm as well as an audio jack. In the first version of the Hard Drive Microphone, the arm is held upright with a pair of springs and vibrates when the cone catches sound.

While the microphone worked, [Rulof] saw room for improvement. In the second version, he replaced the mechanical springs with magnets to keep the arm aloft. One pair was glued to the sides of the base, while another pair recovered from an old optical drive was affixed to the arm. He fabricated a larger paper cone and added a pop filter made out of pantyhose for good measure. The higher sound quality is definitely noticeable. If you are interested in more of [Rulof’s] projects, check out his YouTube channel.

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DIY Bass Drum Microphone Uses Woofer Cone As Diaphragm

Anyone into audio recording knows that recording drums is a serious pain. Mic setup and positioning can make or break a recording session. One particular hurdle is getting a great sound out of the bass drum. To overcome this, [Mike] has built a microphone using an 8″ woofer in an attempt to capture the low-end frequencies of his bass drum. Using a speaker as a microphone isn’t a new idea and these large diaphragm bass drum mics have taken commercial form as the DW Moon Mic and the now-discontinued Yamaha SubKick.

The project is actually quite simple. The speaker’s positive terminal is connected to Pin 2 of a 3-pin XLR microphone connector. The speaker’s negative terminal is connected to the connector’s Pin 1. [Mike] made a bracket to connect the woofer to a mic stand, which in turn was cut down to position the woofer at bass drum height. The setup is then plugged into a mixer or pre-amp just like any other regular microphone.

[Mike] has since made some changes to his mic configuration. It was putting out way too hot of a signal to the preamp so he added an attenuation circuit between the speaker and XLR connector. Next, he came across an old 10″ tom shell and decided to transplant his speaker-microphone from the open-air metal rack to the aesthetically pleasing drum shell. Check out [Mike’s] project page for some before and after audio samples.

Converting Morse Code to Text with Arduino

Morse code used to be widely used around the globe. Before voice transmissions were possible over radio, Morse code was all the rage. Nowadays, it’s been replaced with more sophisticated technologies that allow us to transmit voice, or data much faster and more efficiently. You don’t even need to know Morse code to get an amateur radio license any more. That doesn’t mean that Morse code is dead, though. There are still plenty of hobbyists out there practicing for the fun of it.

[Dan] decided to take a shortcut and use some modern technology to make it easier to translate Morse code back into readable text. His project log is a good example of the natural progression we all make when we are learning something new. He started out with an Arduino and a simple microphone. He wrote a basic sketch to read the input from the microphone and output the perceived volume over a Serial monitor as a series of asterisks. The more asterisks, the louder the signal. He calibrated the system so that a quiet room would read zero.

He found that while this worked, the Arduino was so fast that it detected very short pulses that the human ear could not detect. This would throw off his readings and needed to be smoothed out. If you are familiar with button debouncing then you get the idea. He ended up just averaging a few samples at a time, which worked out nicely.

The next iteration of the software added the ability to detect each legitimate beep from the Morse code signal. He cleared away anything too short. The result was a series of long and short chains of asterisks, representing long or short beeps. The third iteration translated these chains into dots and dashes. This version could also detect longer pauses between words to make things more readable.

Finally, [Dan] added a sort of lookup table to translate the dots and dashes back into ASCII characters. Now he can rest easy while the Arduino does all of the hard work. If you’re wondering why anyone would want to learn Morse code these days, it’s still a very simple way for humans to communicate long distances without the aid of a computer.