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We appreciate your patience as we improve our online experience.
07-18-2019 04:30 AM
Hello everyone,
I am looking for a way to detect outliers of a sensor and delete them from my data. The challenge is, that I don't want to collect a number of data first, to recognize the outliers afterwards, but that with each new measured value it should be recognized whether it is an outlier or not. If it is an outlier, the value should not be displayed.
Attached you will find a vi with real measurement data which simulates the measurment in a for loop. In each cycle of the loop outliers should be recognized and deleted.
The picture shows an example what outliers are.
Any ideas how to go on?
Thanks a lot and best regards,
Michael
Solved! Go to Solution.
07-18-2019 04:48 AM
07-18-2019 06:29 AM
Hello, Gerd,
Thank you very much for your feedback and suggestion. What I forgot to say is that the interesting measurement value can also fluctuate (see picture, red arrows mark the outliers) and is not constant as in the first example. In principle, the process can look like this, i.e. the limits to recognize the outlier have to adapt automatically.
How could one proceed here?
Thank you.
Many greetings
Michael
07-18-2019 06:39 AM
07-18-2019 07:08 AM
Hello Gerd, thank you very much. You gave me the right suggestion. Super!