Fault Isolation Using a Reconstruction Algorithm

Name: Fault Isolation Using a Reconstruction Algorithm
Brand: LAP Lambert Academic Publishing
SKU: 9783659323843
Price: 17209 HUF
Availability: InStock

By Using Auto-Associative Neural Networks

Szerző: Sayyed Hamidreza Mousavi, Mehdi Shahbazian

Nyelv:

Kötés: Puha kötésű

Kiadó: LAP Lambert Academic Publishing

Elérhetőség: Kiadói készleten rendelésre

Küldés 17-27 napon belül

17 209 Ft

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

Információk a könyvről

Szerző

Sayyed Hamidreza Mousavi, Mehdi Shahbazian

Nyelv

Angol

Kötés

Könyv - Puha kötésű

Kiadva

2013

oldal

EAN

9783659323843

Enbook ID

06957689

Kiadó

LAP Lambert Academic Publishing

Súly

147

Méretek

150 x 220 x 5

Teljes leírás

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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Azok a vásárlók, akik ezt a könyvet megvásárolták, a következőket is megvásárolták