Fault Isolation Using a Reconstruction Algorithm

Name: Fault Isolation Using a Reconstruction Algorithm
Brand: LAP Lambert Academic Publishing
SKU: 9783659323843
Price: 51.03 EUR
Availability: InStock

By Using Auto-Associative Neural Networks

Автор: Sayyed Hamidreza Mousavi, Mehdi Shahbazian

Език:

Корици: С меки корици

Издател: LAP Lambert Academic Publishing

Наличност: Налично при издателя, по поръчка

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

Информация за книгата

Автор

Sayyed Hamidreza Mousavi, Mehdi Shahbazian

Език

Английски език

Корици

Книга - С меки корици

Издадена

2013

страници

EAN

9783659323843

Enbook ID

06957689

Издател

LAP Lambert Academic Publishing

Теглоt

147

Размери

150 x 220 x 5

Пълно описание

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

Информация за книгата

Пълно описание

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Клиенти, които купиха тази книга, купиха също