Contents
This chapter presents the application of artificial neural networks discussed in the previous chapters to fault diagnosis of industrial processes. Three examples are considered:
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fault detection and isolation of selected parts of the sugar evaporator,
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fault detection of selected components of the Fluid Catalytic Crackig (FCC) process,
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fault detection, isolation and identification of a DC motor.
In all case studies, locally recurrent globally feedforward networks, introduced in Section 3.5.4, are used as models of the industrial processes considered. Other types of neural networks, discussed in Sections 7.2 and 7.3.3, are used in decision making in order to detect faults.
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© 2008 Springer-Verlag Berlin Heidelberg
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Patan, K. (2008). Industrial Applications. In: Artificial Neural Networks for the Modelling and Fault Diagnosis of Technical Processes. Lecture Notes in Control and Information Sciences, vol 377. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79872-9_8
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DOI: https://doi.org/10.1007/978-3-540-79872-9_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-79871-2
Online ISBN: 978-3-540-79872-9
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