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It all started a few weeks ago with Sparkfun having “20%-off” day, when I got myself (among other things) a BMP085 barometric pressure sensor. When it arrived, I have soldered some pins on it, and set it up with an Arduino Nano, to have the readings off it easily.

View of the circuit — BMP085 barometric pressure sensor breakout board from Sparkfun

Originally all I wanted is just some laid back pressure recording, so maybe I can use that to predict the weather a bit. “Pressure falls: bad weather comes, pressure rises: things will clear up”. I was recording for about a week, and nothing really noteworthy came out of that.

Then it was the news, that the year’s first typhoon is on the way to Taiwan, and it was supposed to be a big one. Obvious that I will try to record the barometric pressure pattern of its passing, but wanted to make it more interesting and informative. More visual than just the timeseries plot of pressures.

The Japanese Meteorological Agency (JMA) is a good place to watch for information about typhoons. They list path prediction, typhoon properties like strength, wind speeds, and central pressure, have satellite imagery. Putting these together, two days before the typhoon arrived, I set up a script to download the satellite imagery as it became available.

Satellite picture of Typhoon Soulik and location of Taiwan on 2013-07-12 morning — The morning before the typhoon arrived

The JMA publishes usually 2 satellite images in an hour for our North Western Quadrant (at :00 and :30), one of them covers the whole area, the other covers just the top 80% or so, leaving a dark band on the bottom. Nevertheless, matching up the pressure reading with the satellite pictures would be a good little project for this time.

Friday came, the government gave the afternoon off, though it turned out no landfall happened till everyone supposed to be off anyways, just a bit of on-and-off rain. People stocked up on convenience store food (I now have a good supply of instant noodles:) and water, taped over their glass windows, take in their plants and BBQ equipment from outside – well, those who have planned.

Around 10pm the big rain has arrived, here’s a video of how it looked from my window. Went to sleep later, and got woken up around 3:30am by the rain having changed into pretty darn big wind. Here’s another video of the violent part of the typhoon that time in the morning, that doesn’t even really do it justice. The houses around here are pretty tall, and I wonder if they have protected from the wind, or been artificial canyons channeling it. Some things got broken, though not as much as I expected – which is a very good thing.

In the meantime by the power of the Internet I have checked out the pressure reading, how is it going a few miles away in the Taipei Hackerspace, where I have left the barometric pressure sensor (the geolocation is 25.052993,121.516981)

Here’s the entire recording of the approximately 2 days of typhoon. It was pretty okay weather in the start and end of the plot.

Plot of pressure readings — Pressure reading during the passing of Typhoon Soulik, recorded at the Taipei Hackerspace

The readings have been corrected to sea level (from about 20m height, where the Taipei Hackerspace is), should be good within 1hPa or less.

The the pressure was indeed dropping like a rock, and the dip on the graph coincided with the most violent wind that woke me up. According the JMA, the central area of the typhoon had pressures down to 950hPa, which means that core must have passed pretty close to here, having readings below 958hPa, though probably not directly, as it didn’t stay down there for long.

I made a video syncing up the pressure reading and the satellite picture. The red dot on the video marks the recording location. (Watching it in full screen and HD makes it clearer.)

I would wonder what was the flat part in the readings while the typhoon was leaving. Maybe sign of changing direction, by the look of it.

Either way, this was fun to do, and I am glad that only a few people got hurt here, much fewer then even during the less powerful typhoons. Maybe getting people scared a little (like with this “super typhoon” stuff that went on) helps them keep safe? Just don’t use it too often.

Extra material

I put almost all material used here into a gist: the satellite imagery download script, the plotting, the movie frame generation, the movie generation script, and the complete barometric recording. Because this last part is pretty big (5Mb), Github truncated the rest of the scripts. I guess it’s okay to check check it out. Will add the Arduino sketch to read the sensor and the logging script later.

The satellite imagery weighs about 60Mb, so don’t put it online, but if anyone wants them, let me know.

Keep safe!

Looks like that one of my specialty as a physicist, and contribution to the labs where I have worked so far, is bringing different kinds of programming techniques, and technologies to the table. I’m not saying I’m any better than many of the professors, post-docs, and students I’ve met so far (there are plenty of ingenious ones), it’s more like I experiment with different tools, have tried more of the cutting edge or recent technologies, did some web programming and could whip up something quick – that might not work very well at first, but does broaden the horizon for the rest of the people.

Also, I’m a lazy person, so want to automate as much as possible. That was on my mind recently when we have been preparing to do a vacuum-system bake-out. It’s essentially a procedure to have a delicate experimental system, mostly made up of steel, glass, and stuff like that, closed up from the atmosphere, all the air pumped out, then heated up to high temperature (~150-300°C). One has to be careful, because things can break, there are temperature limitations for some materials, also on how quickly that temperature can change, requiring careful monitoring of the status of the system. And the whole thing takes something like two weeks or more. Perfect setting for automation.

Set up the electronics

The pressure measurements are done by some expensive other equipment so didn’t have to bother with that one yet, so set to work first on the temperature monitoring. Before it was a bunch of thermocouples and multimeters, requiring manual intervention and lots of labour. Instead, got some inspiration from Adafruit’s Thermocouple Breakout Board, using the MAX31855 chip, and also from the Thermocouple Multiplexer Shield. It can handle only one channel, but can use some other chip together with it to switch between the different thermocouples, and so we can read it out one-by-one. The Adafruit board could only handle 1 channel, and the multiplexer shield was using an older chip for the measurement that I could not buy anymore. In the end, found a good analog multiplexer that one that is sold in the computer market here in Taipei, the CD4067B, and it works pretty well.

Breadboard setup for temperature monitoring Arduino — Breadboard setup for temperature monitoring with Arduino

Of course, setting it all up was quite a bit of fun times, as there were way too many gotchas along the way.

MAX31855 is a surface-mount component, and haven’t worked with it before. Not too bad, and can be much neater, just takes some plactice
MAX31855 is a 3.3V circuit, so the CMOS voltage levels used by my Arduino Mega ADK had to be level shifted
Unlike the older chip, MAX31855 really needs differential input, and it’s much more sensitive to the environment. This required different kind of analog multiplexer than that board had
The Arduino Mega is a new model for me, and had some strange behaviour in terms of the serial communication
Surprisingly there are not too many options for 3.3V voltage regulators over here, just the LM1117, which is different from what others are using elsewhere
Lots of noise and stability issues until figured out what should be how. For example under no circumstance should touch the thermocouple to conducting surfaces, and avoid ground loops
While MAX31855 says it’s “cold-point compensated”, meaning that it accounts for the chip-s local temperature when measuring the thermocouple, it doesn’t appear completely compensated, meaning that we can have unexpected measurement change because the chip is heating up for example by being in a closed box.
Figuring out the right amount of time to wait between switching channels (375ms seems to be good enough, 500ms is totally fine)

In the end, though, we did have a nice 16 channel thermocouple multiplexer, sending off the measurements onto an LCD screen and to the computer over an USB cable.

Temperature monitoring board soldered — Temperature monitoring board in it’s lab setting with 16 thermocouple channels

This is then saved in a database, and can be accessed from elsewhere.

Visualize!

The thing that my co-workers were most amazed by wasn’t the electronics. Sure, they haven’t worked with Arduinos, but did do similar stuff. Instead they liked the monitoring interface much more, this is the one on the picture right here (can click to enlarge)

Bakeout Monitor interface showing the vacuum system, temperatures, pressures and long term graphs — Bakeout Monitor interface (click image for full view)

It’s the schematic layout of our equipment, with the temperatures positioned where the actual sensors are. Also, the change of the measured values in time are also displayed with live scrolling.

I’m not saying it’s great. Thinking about it, the major insight that made it good for the rest of the people is that I realized how much more people understand visual data: the placement of the values to the corresponding locations on the schematics. That’s the only thing.

So inside it’s a MongoDB database (learned from previous mistakes, using a replica-set at least), with Python scripts talking to the sensors and saving the data, NodeJS / Smoothie Charts for visualization (and plain old CSS positioning of <input> tags for the reading display), nginx‘s upstream module for running two monitoring servers just in case. It’s mostly in the Github repo of the monitoring code, as well as the Arduino sketch for talking to the electronics.

It was actually quite fun to write it all, and the gradual improvements, trying the new tech, trying not to lose to much data, amazed how well it works. Especially had a good time learning about the database, scaling, fault tolerance, performance…

Of course there could be room for a lot more improvements.

My failover-restart bash scripts are awful, though they do seem to work more or less and counteract the USB unreliablilities
There were some changes to Smoothie Charts that I could improve on: logarithmic plotting, some display enhancements, wonder if it can be more optimized for performance
More efficient data loading. 12h data is about 30Mb in JSON format, that I send compressed, apparently it gets down to ~5% in size, but it still takes quite a bit of time to process on the frontend
The layout now can be changed from config files if the sensors change, so co-workers can do that without programming knowledge. I wonder if that can be simplified even more

Of course, I’m a person who generally overengineers stuff, so maybe it’s good to stop somewhere. And the somewhere might be when I got to the point to use my Kindle for monitoring (craps out on 1h data already, but some real time things are good enough).

Bakeout Monitor interface running on Kindle — Bakeout Monitor on running on Kindle 3, not perfect but does work

Get on with it

I did learn a lot along the way, and I’m sure that with this experience I will be let to do a little bit more in the lab in terms of programming ideas. I don’t like that the rest of the system is currently forced to be LabView, but that’s for another post, and there are so many things that can be improved in general as well. Let’s just go and do that.