Steady state data filtering

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Vick
Vick on 3 Nov 2017
Commented: Greg Dionne on 28 Dec 2017
Hi,
In the above image i need to filter steady state data( 1,2,3,4), which may contain noisy data as well. Visually i can see the points stabilized at 1750,2250,3500 and 5500, but how to do that programatically. As an output i need the start and end index of the steady state points(noisy data should be removed as well). I can able to specify the tolerance as 3%.

Accepted Answer

Star Strider
Star Strider on 3 Nov 2017
If you have R2016a or later, the Signal processing Toolbox findchangepts (link) function may do what you want.
  2 Comments
Star Strider
Star Strider on 3 Nov 2017
I would do a fft (link) of your signal to get its spectral characteristics. It would seem that the signal transitions are low-frequency, so the high-frequency noise should be easy to filter out. If you have a signal processing background, you can use a linear-phase FIR filter with the filter (link) function to filter your signal. Probably the easiest way to do this is to ask your colleague to give you the coefficients of such a filter that meets your design requirements. (It’s been a while since I manually designed filters, so I won’t attempt to describe those calculations here.)

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More Answers (1)

Greg Dionne
Greg Dionne on 1 Dec 2017
If you have a version of MATLAB beyond R2017b you can try removing outliers with filloutliers and subsequently use ischange.
I think the following syntax is what you would want for ischange:
[TF,S1] = ischange(...) also returns information about the line segments in between change points. For example, [TF,S1] = ischange(A) returns a vector S1 containing the mean of data between change points of a vector A.
  2 Comments
Greg Dionne
Greg Dionne on 28 Dec 2017
Hi Vick,
It seems I missed your reply. Hopefully you've worked past this issue, but if not, could you post your data?

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