I'm trying to classify states with a 1D-CNN-Network structure. Therefore I need to analyze the incoming vibrational data in a certain window. Two examples of such signals are shown below.
I'm continuously streaming the vibrational data. It should be possible to detect a trigger to determine the starting point of the process. This ensures that only interesting states are analyzed and classified. My first approach for such an trigger detection was a rolling window with an average value. If this average value exceeds a certain threshold value, the trigger is set. But this window must be relatively large, because some signals stand still for a longer time (see second picture).
Each process have a different duration between 45s-85s. Therefore it would be perfect to get a trigger for the starting and for the end point of the process. The signal value for stall can be seen at the beginning and at the end of each graph. A single peak (caused from a collision) should not be detected as a trigger.
Which other algorithms would be useful for this application?