The best way to collect the data of sensors over a long period of time to study the behavior of the sensors as to which sensor leads/lags during time transitions?

I have tons of data(in the form of matfiles) where I'm trying to study the behavior of two data output value (Values are Day = 1; Night = 2)for (sensors a; sensor b). Each signal is capable of detecting the transitions from day to night and night to day. I want to capture the transition of time from "day to night" and "night to day" for the two sensor and compare the two to see which sensor lead/lags at transitioning times. I will use "sensor a" as the base sensor. I want to store the results in a way to see these transitions and at the times they are happening. I looked at timesseries and adding events of the transitions. Any suggestions?

Answer 1

[dpb]

If have Signal Processing TB, sounds like job for finddelay

[Brandon Leonard]

Sorry for the confusion with words. They are not signals, just represent to variables that data are being collected for. I called them signals because they are sensors of a vehicle

[dpb]

That's fine; treat as such; it's as if you had a very coarse A/D but the pattern-matching doesn't care about absolute magnitude nor from whence came the data; "numbers is numbers" to it.

It may not work, but I'm betting it will...

[Brandon Leonard]

Okay, thank you dpd!! I will give it a try.

[dpb]

Let us know how it works...