matlab-deep-learning/Industrial-Machinery-Anomaly-Detection
Extract features and detect anomalies in industrial machinery vibration data using a biLSTM autoencoder
This project helps operations engineers and maintenance teams proactively identify potential failures in industrial machinery. It takes vibration data from your equipment and pinpoints unusual patterns that could indicate an emerging problem. The output helps you prioritize maintenance before a costly breakdown occurs.
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Use this if you need to automatically monitor the health of industrial machines using their vibration data to detect early signs of anomalies.
Not ideal if your machinery doesn't produce vibration data or you are looking for root cause analysis rather than just anomaly detection.
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MATLAB
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Last pushed
Sep 30, 2021
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