This workflow tests the performance of previously trained auto-regressive models for anomaly detection: - Filter the data to the maintenance window - Loop over each frequency column - Apply the previously trained model to the data - Calculate 1st level alarms based on the prediction errors - Calculate 2nd level alarms as the moving average of the 1st level alarms - Visualize the 2nd level alarms in a stacked area chart (all sensors) and a line plot (one sensor)