Josef “Jeff” Sipek

Garmin G1000 Data Logging

About a month ago I talked about using R for plotting GPS coordinates. Recently I found out that the Wikipedia article: Cessna 172 I fly in has had its G1000 avionics updated. Garmin has added the ability to store various flight data to a CSV file on an SD card every second. Aside from the obvious things such as date, time and GPS latitude/longitude/altitude it stores a ton of other variables. Here is a subset: indicated airspeed, vertical speed, outside air temperature, pitch attitude angle, roll attitude angle, lateral and vertical G forces, the NAV and COM frequencies tuned, wind direction and speed, fuel quantity (for each tank), fuel flow, volts and amps for the two buses, engine RPM, cylinder head temperature, and exhaust gas temperature. Neat, eh? I went for a short flight that was pretty boring as far as a number of these variables are concerned. Logs for cross-country flights will be much more interesting to examine.

With that said, I’m going to have fun with the 1-hour recording I have. If you don’t find plotting time series data interesting, you might want to stop reading now. :)

First of all, let’s take a look at the COM1 and COM2 radio settings.

> unique(data$COM1)
[1] 120.3
> unique(data$COM2)
[1] 134.55 120.30 121.60

Looks like I had 3 unique frequencies tuned into COM2 and only one for COM1. I always try to get the Wikipedia article: ATIS on COM2 (134.55 at KARB), then I switch to the ground frequency (121.6 at KARB). This way, I know that COM2 both receives and transmits. Let’s see how long I’ve been on the ATIS frequency…

> summary(factor(data$COM2))
 120.3  121.6 134.55 
     1   3303     70 

It makes sense, between listening to the ATIS and tuning in the ground, I spend 70 seconds listening to 134.55. The tower frequency (120.3 at KARB) showed up for a second because I switched away from the ATIS only to realize that I didn’t tune in the ground yet. Graphing these values doesn’t make sense.

I didn’t use the NAV radios, so they stayed tuned to 114.3 and 109.6. Those are the Salem and Jackson VORs, respectively. (Whoever used the NAV radios last left these tuned in.)

To keep track of one’s altitude, one must set the Wikipedia article: altimeter to what a nearby weather station says. The setting is in Inches of Mercury. The ATIS said that 30.38 was the setting to use. The altimeter was set to 30.31 when I got it. You can see that it took me a couple of seconds to turn the knob far enough. Again, graphing this variable is pointless. It would be more interesting during a longer flight where the barometric pressure changed a bit.

> summary(factor(data$BaroA))
30.31 30.32 30.36 30.38 
  262     1     1  3110 

Ok, ok… time to make some graphs… First up, let’s take a look at the outside air temperature (in °C).

> summary(data$OAT)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
    4.0     6.8    12.2    11.5    16.0    18.5 

OAT

In case you didn’t know, the air temperature drops about 2°C every 1000 feet. Given that, you might be already guessing, after I took off, I climbed a couple of thousand feet.

altitude

Here, I plotted both the altitude given by the GPS (Wikipedia article: MSL as well as Wikipedia article: WGS84) and the altitude given by the altimeter. You can see that around 12:12, I set the altimeter which caused the indicated altitude to jump up a little bit. Let’s take a look at the difference between the them.

altitude difference

Again, we can see the altimeter setting changing with the sharp ~60 foot jump at about 12:12. The discrepancy between the indicated altitude and the actual (GPS) altitude may be alarming at first, but keep in mind that even though the altimeter may be off from where you truly are, the whole air traffic system plays the same game. In other words, every aircraft and every controller uses the altimeter-based altitudes so there is no confusion. In yet other words, if everyone is off by the same amount, no one gets hurt. :)

Ok! It’s time to look at all the various speeds. The G1000 reports indicated airspeed (IAS), true airspeed (TAS), and ground speed (GS).

speed

We can see the taxiing to and from the runway — ground speed around 10 Wikipedia article: kts. (Note to self, taxi slower.) The ground speed is either more or less than the airspeed depending on the wind speed.

Moving along, let’s examine the lateral and normal accelerations. The normal acceleration is seat pushing “up”, while the lateral acceleration is the side-to-side “sliding in the seat side to side” acceleration. (Note: I am not actually sure which way the G1000 considers negative lateral acceleration.)

acceleration

Ideally, there is no lateral acceleration. (See Wikipedia article: coordinated flight.) I’m still learning. :)

As you can see, there are several outliers. So, why not look at them! Let’s consider an outlier any point with more than 0.1 G of lateral acceleration. (I chose this values arbitrarily.)

> nrow(subset(data, abs(LatAc) > 0.1))
[1] 41
> nrow(subset(data, abs(LatAc) > 0.1 & AltB < 2000))
[1] 28

As far as lateral acceleration goes, there were only 41 points beyond 0.1 Gs 30 of which were below 2000 feet. (KARB’s pattern altitude is 1800 feet so 2000 should be enough to easily cover any deviation.) Both of these counts however include all the taxiing. A turn during a taxi will result in a lateral acceleration, so let’s ignore all the points when we’re going below 25 kts.

> nrow(subset(data, abs(LatAc) > 0.1 & GndSpd > 25))
[1] 26
> nrow(subset(data, abs(LatAc) > 0.1 & AltB < 2000 & GndSpd > 25))
[1] 13

Much better! Only 26 points total, 13 below 2000 feet. Where did these points happen? (Excuse the low-resolution of the map.) You can also see the path I flew — taking off from runway 6, making a left turn to fly west to the practice area.

acceleration

The moment I took off, I noticed that the Wikipedia article: thermals were not going to make this a nice smooth ride. I think that’s why there are at least three points right by the highway while I was still climbing out of KARB. The air did get smoother higher up, but it still wasn’t a nice calm flight like the ones I’ve gotten used to during the winter. Looking at the map, I wonder if some of these points were due to abrupt power changes.

Here’s a close-up on the airport. This time, the point color indicates the amount of acceleration.

acceleration

There are only 4 points displayed. Interestingly, three of the four points are negative. Let’s take a look.

                    Time LatAc  AltB  E1RPM
2594 2013-05-25 12:52:10 -0.11 879.6 2481.1
2846 2013-05-25 12:56:31 -0.13 831.6  895.8
2847 2013-05-25 12:56:32  0.18 831.6  927.4
2865 2013-05-25 12:56:50 -0.13 955.6 2541.5

The middle two are a second apart. Based on the altitude, it looks like the plane was on the ground. Based on the engine RPMs, it looks like it was within a second or two of touchdown. Chances are that it was just nose not quite aligned with the direction of travel. The other two points are likely thermals tossing the plane about a bit — the first point is from about 50 feet above ground the last is from about 120 feet. Ok, I’m curious…

> data[c(2835:2850),c("Time","LatAc","AltB","E1RPM","GndSpd")]
                    Time LatAc  AltB  E1RPM GndSpd
2835 2013-05-25 12:56:20 -0.02 876.6 1427.9  66.71
2836 2013-05-25 12:56:21  0.01 873.6 1077.1  65.71
2837 2013-05-25 12:56:22  0.01 864.6  982.4  64.21
2838 2013-05-25 12:56:23  0.04 861.6  994.1  62.77
2839 2013-05-25 12:56:24  0.01 858.6  982.6  61.54
2840 2013-05-25 12:56:25  0.01 852.6  988.2  60.18
2841 2013-05-25 12:56:26 -0.02 845.6  959.0  58.91
2842 2013-05-25 12:56:27  0.00 846.6  945.5  57.73
2843 2013-05-25 12:56:28  0.01 844.6  930.9  56.53
2844 2013-05-25 12:56:29  0.10 834.6  908.0  55.16
2845 2013-05-25 12:56:30 -0.01 827.6  886.6  54.16
2846 2013-05-25 12:56:31 -0.13 831.6  895.8  52.71
2847 2013-05-25 12:56:32  0.18 831.6  927.4  51.49
2848 2013-05-25 12:56:33 -0.06 831.6  982.0  50.21
2849 2013-05-25 12:56:34  0.05 840.6 1494.0  49.39
2850 2013-05-25 12:56:35 -0.07 833.6 2249.7  48.76

The altitudes look a little out of whack, but otherwise it makes sense. #2835 was probably the time throttle was pulled to idle. Between #2848 and #2849 throttle went full in. Ground was most likely around 832 feet and touchdown was likely at #2846 as I guessed earlier.

Let’s plot the engine related values. First up, engine RPMs.

RPM

It is pretty boring. You can see the ~800 during taxi; the 1800 during the runup; the 2500 during takeoff; 2200 during cruise; and after 12:50 you can see the go-around, touch-n-go, and full stop.

Next up, cylinder head temperature (in °F) and exhaust gas temperature (also in °F). Since the plane has a 4 cylinder engine, there are four lines on each graph. As I was maneuvering most of the time, I did not get a chance to try to lean the engine. On a cross country, it be pretty interesting to see the temperature go up as a result of leaning.

CHT

EGT

Moving on, let’s look at fuel consumption.

fuel quantity

This is really weird. For the longest time, I knew that the plane used more fuel from the left tank, but this is the first time I have solid evidence. (Yes, the fuel selector was on “Both”.) The fuel flow graph is rather boring — it very closely resembles the RPM graph.

fuel flow

Ok, two more engine related plots.

oil temperature

oil pressure

It is mildly interesting that the temperature never really goes down while the pressure seems to be correlated with the RPMs.

There are two variables with the vertical speed — one is GPS based while the other is barometer based.

vertical speed

As you can see, the two appear to be very similar. Let’s take a look at the delta. In addition to just a plain old subtraction, you can see the 60-second moving average.

vertical speed: GPS vs. Barometer

Not very interesting. Even though the two sometimes are off by as much as 560 feet/minute, the differences are very short-lived. Furthermore, the differences are pretty well distributed with half of them being within 50 feet.

> summary(data$VSpd - data$VSpdG)
     Min.   1st Qu.    Median      Mean   3rd Qu.      Max. 
-559.8000  -49.2800    0.4950    0.8252   53.0600  563.4000 
> summary(SMA(data$VSpd - data$VSpdG),2)
     Min.   1st Qu.    Median      Mean   3rd Qu.      Max.      NA's 
-240.2000  -22.2200    0.6940    0.8226   25.4700  226.7000         9 

Ok, last but not least the CSV contains the pitch and roll angles. I’ll have to think about what sort of creative analysis I can do. The only thing that jumps to mind is the mediocre S-turn around 12:40 where the roll changed from about 20 degrees to -25 degrees.

Roll

Pitch

I completely ignored the volts and amps variables (for each of the two busses), all the navigation related variables (waypoint identifier, bearing, and distance, Wikipedia article: HSI source, course, Wikipedia article: CDI/Wikipedia article: GS deflection), wind (direction and speed), as well as ground track, magnetic heading and Wikipedia article: variation, GPS fix (it was always 3D), GPS horizontal/vertical alert limit, and WAAS GPS horizontal/vertical protection level (I don’t think the avionics can handle WAAS — the columns were always empty). Additionally, since I wasn’t using the autopilot, a number of the fields are blank (Autopilot On/Off, mode, commands).

Ideas

A while ago I learned about CloudAhoy. Their iPhone/iPad app uses the GPS to record your flight. Then, they do some number crunching to figure out what kind of maneuvers you were doing. (I contacted them a while ago to see if one could upload a GPS trace instead of using their app, sadly it was not possible. I do not know if that has changed since.) I think it’d be kind of cool to write a (R?) script that’d take the G1000 recording and do similar analysis. The big difference is the ability to use the great number of other variables to evaluate the pilot’s control of the airplane — ranging from coordinated flight and dangerous maneuvers (banking too aggressively while slow), to “did you forget to lean?”.

Update (2016-10-10): Out of the blue, I got an email from the CloudAhoy guys letting me know that a lot has changed since I wrote this post three and a half years ago and that they support uploading of lots of different flight data file formats. They seem to have some very interesting ways of visualizing the data. I think I’ll have to play with it in the near future.

10 Comments »

  1. Hello Jeff: Your article is very interesting. I have been recording all flights in a Cessna T182T since the g1000 upgrade, however I have not found a friendly software to graph all this information. Could you tell me which one you are using? Thanks, Juan

    Comment by Juan Vargas — May 31, 2013 @ 19:13

  2. Sadly, I don't. All my graphs and analysis is entirely done by hand using R (http://www.r-project.org/). Any spreadsheet application should get you enough to plot the variables over time, or possibly pre-process the data for consumption by something like Google Earth.

    Comment by JeffPC — June 3, 2013 @ 02:35

  3. Hi, I'm trying to figure out the syntax of R so I can graph EGT exactly how you did. Can you list the code you used to plot all of the EGT values on the same graph? Thanks!

    Comment by Marty — June 8, 2013 @ 00:43

  4. I just posted the code in a separate post. http://blahg.josefsipek.net/?p=473 Have fun!

    Comment by JeffPC — June 9, 2013 @ 19:41

  5. Hi Jeff,

    I´m very interested to get the .csv file from my garmin G1000. I´don`t know how I can get the stored data. Can you tell me in which of the SD cards I can find it or even better what do I have to do to store the fligth telemetry data on the SD card in the G1000?

    That would be great!

    Best,
    micha

    Comment by Michael Quetting — September 16, 2014 @ 13:09

  6. Michael,

    Sorry, I can't simply because I don't remember (it's been a while) and I don't have the G1000 manual around. It's one of the slots on the MFD.

    Jeff.

    Comment by JeffPC — October 2, 2014 @ 21:56

  7. Just a couple of things that may be of help.

    GPS altitude should not show above baro altitude. I can see that the GPS altitude changed when you set the baro setting, which is strange? I have no experience with GPS altitude in G1000 though so it might be something here I am not getting.

    On the left/right tank usage on 172, I believe the fuel return is coming into the right tank so it is normally fuller on 172's.

    Do you know how long time period is being stored on the SD card? I only now realized that data is being logged and I am away for a couple of weeks so wonder if the data from my last trip will be there when I get back.

    Comment by Aksel — July 25, 2015 @ 16:26

  8. Hi Jeff,

    Thank you for this interesting article. Could you, please, put on your website or sent me a example of a data logging .csv file. I would like to check the data parameters AFCS roll/pitch commands even if you did not use autopilot. I would like to know if we could find the pilot's inputs or the aircraft flight control surfaces positions (aileron, rudder, elevator, trim). If it's possible, we could be able to analyse the dynamic behavior of the aircraft and then improve simulation models to have one more realistic.

    Thanks.

    Franck

    Comment by Franck — May 30, 2016 @ 19:31

  9. Interesting idea. I'll send you one of the files, but beware... based on my quick glance it looks like (1) I never used the autopilot while logging, and (2) there is only roll/pitch data and nothing related to actual control surfaces.

    Comment by JeffPC — June 1, 2016 @ 12:46

  10. Aksel,

    Thanks for info! As far as I know, the data stays on the SD card "forever". That is, the G1000 doesn't remove it. If I remember correctly, once the SD card fills up the G1000 simply stops logging.

    Good catch about the GPS altitude jumping - it doesn't make sense. Sadly, I don't have access to the plane anymore, and so I'm not inclined to dig into this more.

    Comment by JeffPC — April 30, 2017 @ 13:23

Atom feed for comments on this post.

Leave a comment

Powered by blahgd