Forwarded my Integrated-Vision.com domain to this Blog page.

Godaddy stopped providing hosting many years ago,  I was mad at them for dropping it,  so I didn't have website.  

My plan is to create an official site, with access my library of ELF reading, which is spotty, but does cover several years of measurements.  Mainly with the same receiver.  

For now I only have the important ones available in this blog.  See previous entries for reading that I have sonified.

The ELF receiver has a 3.3V level asynchronous serial output at 9600 baud.  It can be connected to almost any computer using a USB serial converter.  The ones I use have 3.3V and 5V sources and you jumper the Vcc of the converter to the 3.3V. The 5V source is also sent to the receiver to power it.  

The host computer controls the amplification and DC offset of the signal, along with the sampling rate.  The gain of the unit has a range from 28 to ~40,000 times  Some of the gain. up to 32x, can be provided by the TI MSP430F2013 microcontroller which also does the 16bit analog to digital conversion.  Power and serial data are connected to the unit using RJ11 4 conductor telephone cable.  I've been running mine with about 70' of cable between the receiver and my raspberry Pi.  The serial lines can be directly connected to the GPIO pins for /dev/serial0, but I use the USB dongle to protect the board.  

The control software is written in Python and ran in a Jupyter Notebook on either a Raspberry Pi or PC computer. Jupyter was great for experimentation but not for automation.  Notebook has FFT for a small window, 3d FFT plot for entire measurement and spectrogram.  

Also working on a portable communications unit, based on a ESP32 microcontroller board that has WiFi and LORA wireless connectivity.

The received signal can be displayed on the OLED display, saved to micro SD card or published over WiFi to a Mosquito broker. 

I have a Python application on my android phone, that subscribes to the data and plots both the raw signal and a 4 sample running average.  The averaging effectively removes the 60 Hz noise.

Since the received frequencies are so low, ~5 to 40 Hz, I further process the audio to pitch shift it by 16 time (4 octaves) so it can be heard.  

Sonified ELF signals from California, Hawaii and Virgin Island locations with 16x frequency shift

Much of my ELF measurement was done at my home using a 150' pine tree as antenna.

During the recording, there was a power failure at 30s in that ended at 54s.

See previous post for all the gorey details.

This version has the frequency shifted by 16 times, 4 octaves, to make it more audible.

Sonified 16x during power failure 

Additional ELF reading using the new portable ELF receiver and ESP32 based controller.

Waimea canyon lookout parking lot

 using myself as antenna with belt.

Map of location: 22°04'17.3"N 159°39'43.9"W

Sonified audio: 2023-04-22-02_11_30-Waimea

Top plot: Signal plot, green raw and red filtered. 

Bottom plot is frequency spectrum of first ~2 seconds of signal

FFT 3D plot of entire signal, X axis is frequency, Y axis is time and Z is strength.

Blue Beard's castle, St. Thomas, Virgin Islands, USA, 

On 2023-05-12 18:47, also using belt and myself as antenna on the roof.  The receiver is using 

Map of location: 18°20'25.1"N 64°55'26.8"W

Sonified audio: 2023-05-12-18_47_28-BlueBeardsCastle

Sandy Cay, British Virgin Islands

On 2023-05-18 07:36, using belt on small palm tree with 3 times around as antenna.

Sonified audio: 2023-05-18-07_36_09-SandCay

Map of location: 18°26'11.7"N 64°42'39.3"W

Picture of palm tree on Sandy Ca, there were 5 palms visible on east side and this was the north most and easiest to reach barefoot. The hermit crab that lived under wasn't to threatening.  

Plot of one of the readings:

Sonification of Extremely Low Frequency signal

Extremely Low Frequency radio receiver update

After all these years, I finally have a good recording of the Extremely Low Frequency (ELF) radio signals. 

I use a 100' tall pine tree in front of my house as an antenna, by wrapping it with a coil of wire.  Unfortunately, there is a power pole right across the street from it.  So I mainly see 60Hz power signals with some extra wiggles in it.

I have a very good way of removing the power frequency and get a signal that is around 1/10th of the raw signal.

The Schumann frequencies are approximately: 7.8, 15,6, 22 and 28 Hz.  I can see these frequencies, but when I look at the spectrograph, I was expecting to see continuous bars at these frequencies, but they come and go.   

To get a better feel of the signal, I tried to listen to the filtered recording, but it was much too low in frequency, even with headphones.   If I speed up the playback It makes a very interesting sound, because frequencies of the signals are increased to the hearing range.  Of course it loses its timing.  I had taken an online Stanford class, actually from a Spanish university,  Universitat Pompeu Fabra, Barcelona Music Technology Group, where they provided Python code that allows shifting the frequency of a signal to higher frequencies using a sinusoidal model.  I use these tools to upscale the frequency 8 times.  So a 5 Hz tone would become 40 Hz, etc.

During the first atmospheric river storm, we had a short blackout for ~30 seconds.  My house has a solar battery power backup, I recorded the event.  

I always wondered if the signals I was recording were just noises from the power line, because they are quite chaotic.  But now I have a signal with greatly reduced power line noise, still some, because I had power.

In the attached a 2 minute recording, it starts with the power on, after 30 seconds the power is off, until 54 seconds, when power is restored.  

The top plot shows the raw signal in green with the 60 Hz filtered signal in blue.  The blue signal, while reduced, is still there with the power off. 

The middle plot shows a small zoomed 2 second section of 2 the minute recording, which is the filtered signal.

Under it is a frequency spectrum for that 2 seconds.

Here is the Sonification of power failure with 8 times frequency shift, 3 octaves, as a playable 2 minute wave format file.

I had to increase the sample rate from 240 sps to 8000 sps in the sonified version to support the higher frequencies  There was quite a bit of noise as the power glitched before going off.

Update 

Found a python package that uses FFT to shift the pitch of the signal.  I've switched to doing 16 times, 4 octave shift: Sonified 16X audio