Deep Unsupervised Anomaly Detection Applied to Motor-Driven Blowers
In the rapidly evolving Industry 4.0 space, predictive maintenance is shifting towards data-driven techniques. This shift is driven by advanced computing, reduced costs of sensing, abundantly available data as well as maturing machine learning algorithms. In particular, deep learning, a subset of ma...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2022
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| Online Access: | https://hdl.handle.net/1721.1/143291 |