This demo shows how to prepare, model, and deploy a deep learning LSTM based classification algorithm to identify the condition or output of a mechanical air compressor.
This demo shows the full deep learning workflow for an example of signal data. We show how to prepare, model, and deploy a deep learning LSTM based classification algorithm to identify the condition or output of a mechanical air compressor. We show examples on how to perform the following parts of the Deep Learning workflow:
This example shows how to extract the set of acoustic features that will be used as inputs to the LSTM Deep Learning network. To run:
This example shows how to train LSTM network to classify multiple modes of operation that include healthy and unhealthy signals. To run:
This example shows how to generate optimized c++ code ready for deployment.
To run: