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Spatio-Temporal Abnormality Diagnosis for Industrial Distributed Parameter Systems
By Yun Feng
0 - Default Title
Description
The main contents of this book include: 1) Model-based abnormality diagnosis and identification for completely-known industrial DPSs ("white box"); 2) Combined model-based and data-driven abnormality detection and localization for partially-known industrial DPSs ("grey box"); 3) Purely data-driven modeling and diagnosis for completely-unknown DPSs("black box"). In conclusion, this book summarizes the authors’ works on both model-based and data-driven perspectives for S-T abnormality diagnosis of industrial DPSs. To be more precise, this book mainly focuses on the following challenges: space-time couple characteristics, limited sensing in space, and the dynamically varying abnormality in space. This book aims at post-graduate students, researchers, and engineers with background knowledge of industrial systems modeling and monitoring. Interesting readers can obtain state-of-the-art methods systematically in the last 5 years and have a general overview of recent developments and the future direction of this specific research field.
Product details
Number of Pages:
276
Release Date:
2026-01-25
Publication Date:
2026-01-25
Publisher:
Springer
Languages:
Original:
English
ISBN10:
9819537495
ISBN13:
9789819537495
GPSR Manufacturer Reference:
Weight:
630 g
Height:
160 cm
Width:
241 cm
Thickness:
20 cm
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