Statistical Monitoring of Processes with Multiple Operating Modes
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DOI: 10.1016/j.ifacol.2019.06.134
Abstract: Abstract Varying production regimes and loading conditions on equipment often result in multiple operating modes in process operations. The data recorded from such processes will typically be multimodal in nature leading to challenges in applying… read more here.
Keywords: operating modes; statistical monitoring; multiple operating; monitoring ... See more keywords
Bootstrap Confidence Interval on IOHMM Parameters for System Health Diagnostic Under Multiple Operating Conditions
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DOI: 10.1016/j.ifacol.2020.12.2764
Abstract: Abstract The operating conditions have an important impact on system degradation. This paper uses the Input-Output Hidden Markov Model to represent the system degradation having multiple operating conditions. In this paper the bootstrap method is… read more here.
Keywords: multiple operating; operating conditions; system; system health ... See more keywords
Monitoring of Nonlinear Processes With Multiple Operating Modes Through a Novel Gaussian Mixture Variational Autoencoder Model
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DOI: 10.1109/access.2020.3003095
Abstract: Customized production, quality variation of raw materials and other factors make industrial processes work in multiple operating modes. In general, complex industrial processes have strong nonlinearity under each operating mode. In this paper, a Gaussian… read more here.
Keywords: operating modes; mixture; mixture variational; multiple operating ... See more keywords
Surrogate Modeling of Aerodynamic Simulations for Multiple Operating Conditions Using Machine Learning
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DOI: 10.2514/1.j056405
Abstract: This paper describes a methodology, called local decomposition method, which aims at building a surrogate model based on steady turbulent aerodynamic fields at multiple operating conditions. The various shapes taken by the aerodynamic fields due… read more here.
Keywords: methodology; machine learning; operating conditions; multiple operating ... See more keywords