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03a_​Time_​Series_​AR_​Deployment

Anomaly Detection. Time Series AR Deployment

This workflow deploys a previously trained auto-regressive model for anomaly detection:
- Select the date for deployment. Two months of its past values must be available.
- Loop over each frequency column
- Apply the previously trained auto-regressive 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
- Trigger an action if a 2nd level alarm is active

This workflow deploys a previously trained auto-regressive model for anomaly detection. The input data must include at least 2 monthsof past values. This workflow calls a separate "Send_email_to _start_checkup" workflow in case of a 2nd level alarm. Model deployment and calculating 1st level alarms Calculating 2nd level alarms andtriggering action [500-600]+Amp -> AmpLag = 10loop on all columnsi.e. on all frequency binsfor each sensormoving averageon level 1 alarmsand alarm level 2generation Select a day > Extract 2 months of its pastCall Workflownodegeneration alarm level 1for all time seriesread errorstatsread AlignedData.csvadd original datetime columnNode 350Node 351Column Rename Lag Column Column ListLoop Start Loop End (ColumnAppend) Missing Value Alarm Level 2 Select Day Trigger check up iflevel 2 Alarm =1 Alarm level 1 RegressionPredictor Stats and Models Table Reader CSV Reader Joiner Workflow Reader Workflow SummaryExtractor This workflow deploys a previously trained auto-regressive model for anomaly detection. The input data must include at least 2 monthsof past values. This workflow calls a separate "Send_email_to _start_checkup" workflow in case of a 2nd level alarm. Model deployment and calculating 1st level alarms Calculating 2nd level alarms andtriggering action [500-600]+Amp -> AmpLag = 10loop on all columnsi.e. on all frequency binsfor each sensormoving averageon level 1 alarmsand alarm level 2generation Select a day > Extract 2 months of its pastCall Workflownodegeneration alarm level 1for all time seriesread errorstatsread AlignedData.csvadd original datetime columnNode 350Node 351Column Rename Lag Column Column ListLoop Start Loop End (ColumnAppend) Missing Value Alarm Level 2 Select Day Trigger check up iflevel 2 Alarm =1 Alarm level 1 RegressionPredictor Stats and Models Table Reader CSV Reader Joiner Workflow Reader Workflow SummaryExtractor

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

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On NodePit since: 2023-03-21
Last update: 2024-04-27
Created with KNIME version: v4.5.2
Tags: anomaly detectiontime series analysisauto-regressive modelsIoTInternet of Thingsdeploymentcall workflowpredictive maintenancesensor

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