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Welcome to the Seeq Open Source Gallery

These projects are used in conjunction with Seeq Workbench, Seeq Organizer and Seeq Data Lab.

You are welcome to fork the repositories and make improvements if the project’s license permits you to do so.


Correlation

Maintainer(s): Seeq

Documentation: https://seeq12.github.io/seeq-correlation

GitHub: https://github.com/seeq12/seeq-correlation

Analyze correlations and lags amongst time series signals. Perform offline cross correlation analysis and deploy in Seeq to monitor for correlation and/or lag changes.


Clustering

Maintainer(s): Seeq

GitHub: https://github.com/seeq12/seeq-clustering

Perform visual or automatic clustering of equipment/process data to identify similar periods in time. Both ad hoc and streaming analysis is supported. Similar periods are identified as capsules of a condition in Seeq.


System Identification (SysId)

Maintainer(s): BYU PRISM

GitHub: https://github.com/BYU-PRISM/Seeq

Build dynamic multivariate models from contextualized equipment/process data and deploy in Seeq for historical and streaming predictions.


Multivariate Pattern Search (MPS)

Maintainer(s): Seeq

Documentation: https://seeq12.github.io/seeq-mps/

GitHub: https://github.com/seeq12/seeq-mps

Find similar or dissimilar periods for multivariate continuous and batch processes. Gain insights into key contributors and bad actors.


Azure Machine Learning Integration

Maintainer(s): Seeq

Documentation: https://seeq12.github.io/seeq-azureml/

GitHub: https://github.com/seeq12/seeq-azureml

Enable engineers and process experts to analyze, evaluate and deploy machine learning models built by data scientists in Azure ML Studio.


Stiction Analyzer

Maintainer(s): Process Automation, HAW Hamburg

Documentation: https://haw-process-automation.github.io/Stiction-Analyser/

GitHub: https://github.com/HAW-Process-Automation/Stiction-Analyser

Detect, monitor and analyze oscillation and stiction in control valves.