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.
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));
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.
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(startidx:stopidx), y(startidx:stopidx), 'r.')