Signal recognition with machine learning using wavelet features

The emerging techniques of machine learning and artificial intelligence are making revolutionary changes in all kinds of the industrial world. As a high-tech business solution company, uses these modern techniques to help industrial manufactory companies work more efficiently. One of the challenging problems is to make the computer automatically recognize the status and behavior of the machine from the data collected by different sensors, so that people can record the history of the machine and conduct further analysis. This project tries to develop some algorithms to achieve this goal using the state-of-the-art machine learning technology. The algorithms developed will help the computer learn the patterns of the sensor data first, and recognize/detect the behaviors of the machine automatically.

Faculty Supervisor:

Bin Han


Chenzhe Diao

Partner: Canada Inc




Information and communications technologies




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