Feature Extraction Using Diagnostic Feature Designer App

Use Diagnostic Feature Designer app to extract time-domain and spectral features from your data to design predictive maintenance algorithms.

In this example, measurements have been collected from a triplex pump under different fault conditions. The app lets you import this data and interactively visualize it. You can group the measurements by different fault conditions. After the time-domain and spectral features are extracted from the data, you can evaluate the effectiveness of the extracted features using histograms. You can also rank them to determine numerically which features are likely to best discriminate healthy and faulty behavior. Finally, the most effective features are exported to Classification Learner app for further evaluation of feature effectiveness and for training machine learning models.

Other Resources:
- MATLAB and Simulink for Predictive Maintenance: https://bit.ly/2Tp2yLq
- MATLAB Tech Talks on Predictive Maintenance (5 Videos): https://bit.ly/2XzYIhy
- Analyze and Select Features for Pump Diagnostics: https://bit.ly/2MA6nvv
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