Bike accelerometer data

Instead of coming up with a way to 'correctly' attach my accelerometer onto my electric bike (which has only delayed this project), today I just set the thing recording and threw it in my backpack.

The accelerometer on my phone collects data at about 203Hz, so the highest frequency it can deal with is about 100Hz.

Technical problems failed to record my outbound ride, but my inbound ride was recorded.  Here's the data:

... and here's the spectrogram (using a 256 sampling window in a 4096 pad):

spectral range (left to right) goes from 0 to about 100 Hz.  Temporal range is about 900 seconds, doing from top to bottom.

That bright white wiggly line is about 6 Hz.  This corresponds to the rotational frequency of the tires if traveling about 28 mph -- which I was!  The line is wiggly because I'm contantly slowing down and speeding up.

Check out the harmonics!

Pretty decent S/N -- I think I can work with this...

Here's a plot of the average spectrogram, which is just the sum of each row from the image above.  The peak is about 5.84 Hz, which with 26 inch wheels works out to an average speed of 27.1 mph.  I can't account for those other smaller peaks to the left at about 4 Hz and 1.6 Hz.

Cloud Study

Another project that I'm doing to try to resurrect is my cloud observation project.  The first thing to do was to see if I still had the notes I'd taken over a year ago about configuring the all-sky cameras (that are being used for meteor detection and other astronomical stuff at night) to view the sky during the day and in color.

Luckily, it's all still there.  In fact there were python scripts to set the camera parameters.  I then added a little thing to be able to save the images to disk (which is ok for now).

Anyhow, here's the view from USL00Y -- which is looking towards the northeast.  The image is upside-down since the camera is rotated 180 degrees in it's mount (I don't care what the orientation is):

So now I'll sit back and think about what to do with this.

Here's another image, same camera, taken a few hours after the previous image was taken:

gotta work on colors a little -- this image looks way too red.  As I recall, there's a setting for this.

Out of focus raindrops from USL00Y in 'light' mode:

Monsoon Season 2023

The monsoons are slow to get started this year, but we've already had a couple of fairly decent storms.

My all-sky camera system (USL00X) captured some lightening the other evening:

The all-sky camera system has been having some trouble lately, mainly (I think) due to the heat.  The cameras are pretty indestructable from what I can tell, but the network switch has a max operating temp of 104F and a max storage temp of 158F.  On top of that, the fan controller does not come on (i.e., it will turn off!!) if the temp is above 50C (122F).  So it's probably getting pretty hot in there.

I recently replaced the network switch and that at least allows me to see the cameras.  The system is still running a little flaky, but I'm on it and will get it back to normal operations soon.

First Tau Her Meteor

Image taken at 05:46:46 UTC on 2022-05-28 with USL012.  Radiant is RA = 202.66425, DEC = +16.13974.

Here's another one from 2022-05-29 06:02:30 UTC:

the trail in the extreme upper left is an aircraft.  The meteor is the one just to the right.  Radiant RA = 203.90906, DEC = +18.88696

So cool...

Twilight Derivatives

Since change is the nature of the universe, I'm always interested in looking at how things change.

Measuring how things change is simply looking at the difference between two adjacent data points, either in time or space.

In the case of looking at twilight, I'm interested in seeing how the brightness changes as a function of time.  If you want to put this in terms of motion, the dimming of the sky after sunset is a lot like a velocity.  I can calculate the 'velocity' of the dimming by calculating the derivative, or difference, between two adjacent points in time.

I also like to make various forms of spectra -- also called 'histograms'.  I can make a spectrum of the velocities, and then break them up in time so I can see how the brightness is changing at different times of night.

Here's a recent sunset (x-axis is hours after sunset, y-axis is ADU):

and here are the differences for the same time period:

Notice that the 'velocity' is negative when the brightness is dropping, just as expected.

Here's the entire night's derivatives (x-axis is hours after sunset, y-axis is in ADU per 10 seconds):

I can then divide this up into 1000 second (16m 40s) chunks, and make a spectrum (histogram) of the derivatives:

times goes left to right, top to bottom.

At this point, I'm just looking at the data in as many ways as I can think of.  I'm not interested (yet) in understanding or explaining what I'm seeing with this data.

Maybe there's nothing interesting at all.

One thing I definitely want to do is a running average to smooth the derivative plot a little to see if there's any underlying structure.  If you look at the darkest part of the plot you get an idea of how dynamic the velocity is.

So yeah the velocity is changing, too.

Twilight

Here's one of the things I'm interested in looking at pretty closely -- twilight.

Civil twilight is 0 - 0.5 hours (which is saturated on my camera)

Nautical twilight is 0.5 - 1 hour

Astronomical twilight is 1 - 1.5 hours

I can now confirm with these plots that yes indeed at 1.5 hours after / before sunset / sunrise, the sky is as dark as it's gonna get:

and here's the entire night, zoomed in to show the fuzz:

according to the MMT almanac, moonrise was 7.41 hours after sunset.  I see a brightening of the sky at about 7.0 hours after sunset.  ?????

Sky Brightness

Been recently measuring the brightness of a very small portion of sky a few square arcmin) using one of the meteor cameras -- in this case, USL00X -- over the course of a night.  I plan on making these measurements (clear or cloudy) for at least the next month.  Here's the messy data sofar:

The x-axis the is the number of hours since sunset.  The y-axis is the brightness in ADU which ranges from 0 to 255.  This also shows the curve for the lunar eclipse that recently happened on 16 May 2022 UTC.  That particular curve is hard to see, so I separate it out:

In any case, this is pretty cool data and I'm hoping that I'll be able to see something in this to grab on to.  What initially captured my interest was looking at sunrise and sunset (from a project I did several years ago measuring the color of the set / rise sky at different locations).

Here's a closer look at the data going up to 2 hours after sunset:

... and the two hours before sunrise:

Looking at stuff like this is part of what basic research is all about -- observation and experimentation.

It's also cool that I can correlate sky brightness with lunar rise and set, but also lunar phase!  That last one was a bit of a pleasant surprise.

As I said, the next step is to look and see if there's anything worth grabbing on to.  I'll know I've got something when I start questioning why it is that way and start hunting for an answer.