Data-Driven Fault Detection and Reasoning for Industrial Monitoring
1st ed. 2022
Book Details
Format
Hardback or Cased Book
Book Series
Intelligent Control and Learning Systems
ISBN-10
9811680434
ISBN-13
9789811680434
Edition
1st ed. 2022
Publisher
Springer Verlag, Singapore
Imprint
Springer Verlag, Singapore
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Jan 4th, 2022
Print length
264 Pages
Weight
564 grams
Dimensions
16.20 x 24.10 x 2.50 cms
Product Classification:
Instruments & instrumentation engineeringAutomatic control engineeringArtificial intelligence
Ksh 8,100.00
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This open access book assesses the potential of data-driven methods in industrial process monitoring engineering.
Introduction.- Basic Statistical Fault Detection Problems.- Principal Component Analysis.- Canonical Variate Analysis.- Partial Least Squares Regression.- Fisher Discriminant Analysis.- Canonical Variate Analysis.- Fault Classification based on Local Linear Embedding.- Fault Classification based on Fisher Discriminant Analysis.- Quality-Related Global-Local Partial Least Square Projection Monitoring.- Locality-Preserving Partial Least-Squares Statistical Quality Monitoring.- Locally Linear Embedding Orthogonal Projection to Latent Structure (LLEPLS).- Bayesian Causal Network for Discrete Systems.- Probability Causal Network for Continuous Systems.- Dual Robustness Projection to Latent Structure Method based on the L_1 Norm.
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