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https://github.com/industrial-edge/anomaly-detection-getting-started

Getting-Started tutorial to train a neural network with the Anomaly Detection
https://github.com/industrial-edge/anomaly-detection-getting-started

ai anomaly-detection data-bus data-service flow-creator industrial-edge time-series-analysis

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Getting-Started tutorial to train a neural network with the Anomaly Detection

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README 

        
# Anomaly Detection getting started tutorial 



This example shows how to use the Industrial Edge app "Anomaly Detection" to analyze your automation process. During this tutorial you will go through every single setup step to train a machine learning model on time series input data.



- [Anomaly Detection getting started tutorial](#anomaly-detection-getting-started)

  - [Description](#description)

    - [Overview](#overview)

    - [General task](#general-task)

  - [Requirements](#requirements)

    - [Prerequisites](#prerequisites)

    - [Used components](#used-components)

  - [Configuration steps](#configuration-steps)

  - [Documentation](#documentation)

  - [Contribution](#contribution)

  - [Licence and Legal Information](#license-and-legal-information)



## Description



### Overview



This document describes how to create an Anomaly Detection model. This model is used to detect abnormal behavior in time series data. If an unusual behavior is detected, the app can be used to identify such divergence and in some cases you’ll get a first impression what caused the problem and where to start the further investigation, e.g. to make a deep dive analysis with the Anomaly Detection.

  



![task](docs/graphics/14AnomalyView.PNG)



### General Task



- You will learn how to select the incoming data and how to potentially transform this data in order to come up with a machine learning model 

- After that you will see how to define the model parameters and start the training. 

- In the last step you will use this model for inference and start the Live Anomaly Detection



## Requirements



### Prerequisites

- Access to Industrial Edge Management System (IEM)

- Onboarded Industrial Edge Device (IED) on IEM  



### Used components



* Industrial Edge Device Version simatic-ipc-ied-os-2.0.0-19-x86-64

* Databus V 2.3.1-2

* IIH Essentials V 1.9.0

* Flow Creator V 1.16.0-2

* Anomaly Detection V 1.1.0



## Configuration steps



To successfully run the application, you need to follow these steps:



* [Installation of screwing simulation](/docs/Installation_ScrewSimulation.md)

* [Setup anomaly detection](/docs/Installation.md)



## Documentation



You can find further documentation and help in the following links



* [Industrial Edge Hub](https://iehub.eu1.edge.siemens.cloud/#/documentation)

* [Industrial Edge Forum](https://www.siemens.com/industrial-edge-forum)

* [Industrial Edge landing page](https://new.siemens.com/global/en/products/automation/topic-areas/industrial-edge/simatic-edge.html)

* [Industrial Edge GitHub page](https://github.com/industrial-edge)



## Contribution



Thank you for your interest in contributing. Anybody is free to report bugs, unclear documentation, and other problems regarding this repository in the Issues section.

Additionally everybody is free to propose any changes to this repository using Pull Requests.



If you haven't previously signed the [Siemens Contributor License Agreement](https://github.com/siemens/.github/blob/main/cla/cla.md) (CLA), the system will automatically prompt you to do so when you submit your Pull Request. This can be conveniently done through the CLA Assistant's online platform.

Once the CLA is signed, your Pull Request will automatically be cleared and made ready for merging if all other test stages succeed.



## License and Legal Information



Please read the [Legal information](LICENSE.txt).