Recognise specific pattern in timetable
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I have a timetable logfile from an electrical motor.
This motor runs a variable rounds per minute, according to manual adjustment.
if i plot the entire timeline vs rpm i get what like in attached picture "1".
The intresting part of that data is where you see the rpm drops from ~2250 rpm to ~1300rpm. please see picture "2".
Is it possible to make a code that is recognising this specific pattern automatically, and isolate the time where this is happening? in this case it must be isolated from ~60s to ~100s to isolate this specifik range.
Thanks!
2 Comments
Star Strider
on 9 May 2022
The findsignal function is the only method that I am aware of that would easily do this sort of pattern-matching.
Answers (3)
Mitch Lautigar
on 10 May 2022
After you grab the data, run a simple check to see if the rpm's drastically decrease. This can look something like the following
%rpms_val is the name i'm use for your "y" data points.
%rpms_time is the name i'm going to use for your "x" data points.
rpms_slope = [];
for i = 1:length(rpms_val)-1
rpms_slope(i) = (rpms_val(i+1) - rpms_val(i)) / (rpms_time(i+1)-rpms_time(i));
end
rpms_check = find(rpms_slope < -5) %-5 can be whatever tolerance you want.
from here, you can code in any flags you wish. You can even change the color of the data that is negative.
2 Comments
Mitch Lautigar
on 16 May 2022
rpms_slope(i) = (rpms_val(i+1) - rpms_val(i)) ./ (rpms_time(i+1)-rpms_time(i))
forgot it was vector math. Should fix your issue.
Les Beckham
on 10 May 2022
Edited: Les Beckham
on 10 May 2022
One approach without requiring the Signal Processing Toolbox:
load('answers.mat') % an approximation of your data
x = data(:,1);
y = data(:,2);
startidx = find(y>2000, 1, 'first'); % you may need to adjust this
% The following line may also need to be adjusted if the desired region is
% not strictly decreasing
stopidx = find(diff(y(startidx:end))>1, 1, 'first') + startidx - 1
plot(x,y)
hold on;
plot(x(startidx:stopidx), y(startidx:stopidx), 'r.')
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