Package: seeq-constraintdetection
seeq-constraintdetectionis an Add-on for control loop performance monitoring. It is used to find time periods when a control signal is constrained or saturated. This means that the signal is at its minimum or maximum and only
deviates from there for short time periods. Control signals include all signals which are related to a control loop: Controller output (OP), setpoint (SP), process variable (PV), manipulated variable (MV) and auto-manual mode.
Saturation occurs in the OP whereas constraints occur in the PV and MV due to their physical limitations (e.g. measuring range, actuator range) or in the SP (e.g. when model predictive control is applied). The Constraint Detection
Add-on analyses the OP, SP, PV and MV and and generates a worksheet in treemap view where every controller panel is coloured according to the time-percentage a signal is constrained/saturated in the analysis time period.DocumentationDocumentation forseeq-constraintdetectionUser Guideseeq-constraintdetectionUser Guideprovides an explanation of the required asset tree structure and the workflow in the user interface. The video below gives an introduction about the Constraint Detection Add-on.https://user-images.githubusercontent.com/111488243/192772896-1b0b19a9-c70c-4486-994b-a8a13f5eb830.mp4InstallationThe backend ofseeq-constraintdetectionrequiresPython 3.7or later.DependenciesSeerequirements.txtfile for a list of dependencies and versions. Additionally, you will need to install theseeqmodule with the appropriate version that matches your Seeq server. For more information on theseeqmodule seeseeq at pypi.User Installation Requirements (Seeq Data Lab)If you want to installseeq-constraintdetectionas a Seeq Add-on, you will need:Seeq Data Lab (>=R54.1.6 or >=R56.1.4)seeqmodule whose version matches the Seeq server versionSeeq administrator accessEnable Add-on in the Seeq serverUser Installation (Seeq Data Lab)The latest build of the project can be foundhereas a wheel file. The file is published as a courtesy and does not imply any guarantee or obligation for support from the publisher.Create anewSeeq Data Lab project and open theTerminalwindowRunpip install seeq-constraintdetectionRunpython -m seeq.addons.constraintdetectionFollow the instructions when prompted. ("Username or Access Key" is what you use to log in to Seeq. "Password" is your password for logging into Seeq.)There are additionalOptionsfor the Add-on installation. These include--usersand--groups. These can be used to change permissions for the Add-on Tool.python -m seeq.addons.constraintdetection [--users <users_list> --groups <groups_list>]DevelopmentWe welcome new contributors of all experience levels. The Development Guide has detailed information about contributing code, documentation, tests, etc.Important linksOfficial source code repo:https://github.com/HAW-Process-Automation/Constraint-DetectionIssue tracker:https://github.com/HAW-Process-Automation/Constraint-Detection/issuesSource codeYou can get started by cloning the repository with the command:git clone git@github.com:HAW-Process-Automation/Constraint-Detection.gitInstallation from sourceFor development work, it is highly recommended creating a python virtual environment and install the package in that working environment. If you are not familiar with python virtual environments, you can take a lookhere.Once your virtual environment is activated, you can install requirements andseeq-constraintdetectionfrom source with:pip install -r requirements.txt
python setup.py installSupportCode related issues (e.g. bugs, feature requests) can be created in theissue tracker.Maintainer: Lea TiedemannCitationPlease cite this work as:seeq-constraintdetection v0.0.41
HAW Process Automation
https://github.com/HAW-Process-Automation/Constraint-Detection