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Diagnosis and Prognosis for Complicated Industrial Systems—Part II.

Authors :
Yin, Shen
Ding, Steven X.
Zhou, Donghua
Source :
IEEE Transactions on Industrial Electronics; May2016, Vol. 63 Issue 5, p3201-3204, 4p
Publication Year :
2016

Abstract

This special section on "Diagnosis and Prognosis for Complicated Industrial Systems?Part II? is the continuation of its previous part I (IEEE Transactions on Industrial Electronics, Vol. 63, Issue 4, 2016). The diagnosis and prognosis approaches can be roughly classified into two categories: 1) model-based and 2) data-driven approaches. The model-based approaches perform the diagnosis and prognosis relying on the physical models from first principles, whereas the data-driven approaches make full use of the process data to monitor the systems under consideration. Due to the increasing complexity of the industrial system, new challenges are encountered in diagnosis and prognosis of such complicated systems, and more efficient process monitoring approaches are needed. From this point of view, the papers included in this section are focused on the recent developments of diagnosis and prognosis for complicated industrial systems, providing novel ideas and referential directions for both the academic and industrial communities. [ABSTRACT FROM PUBLISHER]

Details

Language :
English
ISSN :
02780046
Volume :
63
Issue :
5
Database :
Complementary Index
Journal :
IEEE Transactions on Industrial Electronics
Publication Type :
Academic Journal
Accession number :
114509170
Full Text :
https://doi.org/10.1109/TIE.2016.2538745