Autoencoder-based anomaly detection for sensor data

Version 1.1 (547 KB) by Antti
Demo that shows how to use auto-encoders to detect anomalies in sensor data
601 Downloads
Updated 3 Jul 2020

This demo highlights how one can use an unsupervised machine learning technique based on an autoencoder to detect an anomaly in sensor data (output pressure of a triplex pump). The demo also shows how a trained auto-encoder can be deployed on an embedded system through automatic code generation. The advantage of auto-encoders is that they can be trained to detect anomalies with data representing normal operation, i.e. you don't need data from failures.

Cite As

Antti (2024). Autoencoder-based anomaly detection for sensor data (https://github.com/aloytyno/Autoencoder-based-anomaly-detection-for-sensor-data/releases/tag/1.1), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2020a
Compatible with R2015b to R2020a
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
1.1

See release notes for this release on GitHub: https://github.com/aloytyno/Autoencoder-based-anomaly-detection-for-sensor-data/releases/tag/1.1

1.0

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.