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Novelty Detection Of Machinery Using A Non-Parametric Machine Learning Approach, Enrique Angola
Novelty Detection Of Machinery Using A Non-Parametric Machine Learning Approach, Enrique Angola
Graduate College Dissertations and Theses
A novelty detection algorithm inspired by human audio pattern recognition is conceptualized and experimentally tested. This anomaly detection technique can be used to monitor the health of a machine or could also be coupled with a current state of the art system to enhance its fault detection capabilities. Time-domain data obtained from a microphone is processed by applying a short-time FFT, which returns time-frequency patterns. Such patterns are fed to a machine learning algorithm, which is designed to detect novel signals and identify windows in the frequency domain where such novelties occur. The algorithm presented in this paper uses one-dimensional …