Engineering

Telemetry Style Data Analysis

Telemetry Style Data Analysis

Postby Waterbear » Tue Feb 15, 2011 8:13 am
Please come up with a way to analyze standard telemetry style data:

time1, latitude,longitude, eventDescription1, eD2, eD3, ratio, quantity, boolean, descriptive text
time2, ...
.
.
.


This data-set is standard for working engineers, does anyone have any thoughts?
Waterbear
 
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Re: Telemetry Style Data Analysis

Postby IrishLefty » Wed Mar 02, 2011 6:09 pm
A long time ago, when I was a “Working Engineer,” telemetry data included things such as time (even though it was not transmitted with the other telemetric data,) altitude, speed, Lat/Long, temperature, etc. In other words, things that could be measured and transmitted back to the facility doing the analyses. Things such as “Event Descriptions,” or “Descriptive text” were not a part of telemetry, they were added in before or after by the engineers doing the analysis as required.

The quickest method of analysis in “real time” is generally a side-by-side view of all the selected parameters such as you would see on a strip chart recorder. Obviously, a computer analysis of the real time data based on comparisons of different data at specific time relationships would be quicker and more accurate, but I like to use hard copies in real time to get the quickest indication of a problem.

Anyway, I was not quite sure what you were asking for, so I guessed.
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Re: Telemetry Style Data Analysis

Postby Waterbear » Wed May 11, 2011 3:25 am
Yeah, you're right, let me simplify the request ...

Telemetry Stream X:
time1, latitude, longitude, quantity
time2, ...
.
.
.

Could Wolfram Alpha figure out a way to analyze and display this telemetry stream in several different ways (that make sense) and at different time scales?

WA could make decisions about what to display based on the character of quantities in the stream. For example zeros and ones translate to a boolean stream: WA figures this out and produces a series of charts that make sense for a boolean telemetry stream like a pie chart with percentage 'true' and percentage 'false'. Another example, if each quantity is larger than the previous one then a chart showing the delta between sequential telemetry readings would make sense.
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