A Meta-Knowledge Architecture for Planning and Explanation in Repair Domains

Caviedes, Jorge E.; Bourne, J.R.; Brodersen, A.J.; Osborne, Peter; Ross, Abigail; Schaffer, J. D.; Bengtson, G.

doi:10.1007/978-1-4899-2471-1_2

Cited by 1 publication

(1 citation statement)

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“…Efforts have been made to expand the applications to equipment maintenance and diagnostics, science, engineering, agriculture, business, and finance [34,175,198,211,284, 314J. Here we provide an introduction to expert systems.…”

Section: Expert Systemsmentioning

confidence: 99%

Fault Detection and Diagnosis in Industrial Systems

Chiang

Russell

Braatz

2001

Advanced Textbooks in Control and Signal Processing

1,160

811

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An alternative group of methods has emerged which do not require the use of an explicit model. This is the key basic construct for the data-driven paradigm. Model-free and non-parametric methods for fault detection, process optimisation and control design are currently at a particularly exciting stage of development.This new advanced textbook by Chiang, Russell and Braatz primarily tackles the data-driven routes to Fault Detection and Diagnosis. It is an outgrowth of a prior Advances in Industrial Control monograph; Russell, Chiang and Braatz. Data-driven Techniques for Fault Detection and Diagnosis in ChemicalProcesses, 2000, ISBN 1-85233-258-1. The new textbook expands the material of the monograph and gives a fuller presentation of some of the alternative modelbased methods, the analytical methods, and of the knowledge-based techniques. vi Series Editors' ForewordThis allows the reader to compare and contrast the different approaches to the problem of fault detection and diagnosis. Thus the text is suitable for advanced courses for process, chemical and control engineers.

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