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Fall 2014
While there has been much literature in the area of system monitoring and diagnosis, most of these techniques have a relatively small scope in terms of the faults and performance issues that they are built to detect. When implementing several monitors simultaneously on a single process, a single...
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Monitoring of Industrial Processes via Non-stationary Probabilistic Slow Feature Analysis Machine Learning Algorithm
DownloadSpring 2020
This research develops a first of its kind machine learning (ML) algorithm, called probabilistic slow feature analysis (PSFA), that monitors and detects faults for non-stationary industrial processes. The novelty of this ML algorithm is that it can monitor and detect faults for non-stationary...