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I do not know how to define my problem in a short sentence so I can find information on the internet.

I have this sensor data:

RAW sensor data example

I have observed my experiment with a time lapse camera. So i know when the sensors where moving, and when the sensor was steady. And I want to be able to recognize and validate these two groups/classes/categories. So when I am able to do that with my observed experiment data I can apply it on the field data (which I can't observe).

I have searched the internet for : semi-supervised anomaly detection. But I think I am using the wrong terms and definitions. And also the most information I found do not have the advantage of a experiment that can do observed vs. measured.

I think in science this most be a common kind of data analysis but I do not have the right vocabulary to define my questions/problems.

I am using python to analyze my data.

Does anyone know a better definition or knows how to clearly and statistically separate this problem?

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