Fault Isolation Using a Reconstruction Algorithm

Name: Fault Isolation Using a Reconstruction Algorithm
Brand: LAP Lambert Academic Publishing
SKU: 9783659323843
Price: 205.56 PLN
Availability: InStock

By Using Auto-Associative Neural Networks

Autor: Sayyed Hamidreza Mousavi, Mehdi Shahbazian

Język:

Oprawa: Miękka

Wydawca: LAP Lambert Academic Publishing

Dostępność: Na zamówienie

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205.56 zł

Process history based approaches for fault diagnosis has been widely used recently. Principal Compon...

Informacje o książce

Autor

Sayyed Hamidreza Mousavi, Mehdi Shahbazian

Język

Angielski

Oprawa

Książka - Miękka

Data wydania

2013

strony

EAN

9783659323843

Enbook ID

06957689

Wydawca

LAP Lambert Academic Publishing

Waga

147

Wymiary

150 x 220 x 5

Pełny opis

Process history based approaches for fault diagnosis has been widely used recently. Principal Component Analysis (PCA) is one of these approaches, which is a linear approach; however most of the processes are nonlinear. Hence nonlinear extensions of the PCA have been developed. Nonlinear Principal Component Analysis (NLPCA) based on the neural networks is a common method which is used for process monitoring and fault diagnosis. NLPCA based neural networks are implemented using different methods, in this book we apply Auto-Associative Neural Networks (AANN) for implementing NLPCA. This work is aimed towards the development of an algorithm used in conjunction with an Auto Associative Neural Network (AANN) to help locate and reconstruct faulty sensor inputs in control systems. Also an algorithm is developed for locating the source of the process fault.

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Fault Isolation Using a Reconstruction Algorithm

By Using Auto-Associative Neural Networks

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