Kontakt
Kako nakupovati
Dostava
Svetovalec pri nakupu
Fault Isolation Using a Reconstruction Algorithm
By Using Auto-Associative Neural Networks
Angleščina
108 b
30 dni za vračilo blaga
Drugi so kupili tudi
/
Mehka
13.03
€
/
Mehka
20.10
€
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.
O knjigi
Angleščina
Podarite to knjigo še danes
To je povsem preprosto
1 Dodajte knjigo v košarico in izberite dostavo kot darilo 2 V zameno vam bomo poslali kupon 3 Knjiga bo dostavljena na naslov obdarovancaMorda bi vas zanimalo tudi
/
Mehka
17.47
€
/
Mehka
14.04
€
/
Mehka
6.36
€
/
Mehka
18.28
€
/
Mehka
165.31
€
/
Mehka
14.34
€
/
Adobe ePub DRM
18.28
€
