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Journal ArticleDOI

Recursive transformed component statistical analysis for incipient fault detection

TLDR
Compared with existing multivariate statistical process monitoring approaches such as principal component analysis (PCA) and its variants, the superior detectability of RTCSA is illustrated by a numerical example and the Tennessee Eastman process.
About
This article is published in Automatica.The article was published on 2017-06-01. It has received 124 citations till now. The article focuses on the topics: Principal component analysis & Wishart distribution.

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Citations
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Some modified matrix eigenvalue problems.

Gene H. Golub
TL;DR: This work considers the numerical calculation of several matrix eigenvalue problems which require some manipulation before the standard algorithms may be used, and studies several eigen value problems which arise in least squares.
Journal ArticleDOI

Incipient fault detection with smoothing techniques in statistical process monitoring

TL;DR: Wang et al. as discussed by the authors proposed two representative smoothing techniques, which are based on a generic fault detection index in multivariate statistical process monitoring (MSPM), to detect incipient faults.
Journal ArticleDOI

Fault-Tolerant Cooperative Control of Multiagent Systems: A Survey of Trends and Methodologies

TL;DR: A survey of trends and methodologies of fault tolerant cooperative control in multiagent systems finds that multiple agents can provide much more redundancy than a single agent system, thereby making the fault tolerance cooperative control design more flexible.
Journal ArticleDOI

A Review on Fault Detection and Process Diagnostics in Industrial Processes

TL;DR: Current research and developments of F DD approaches for process monitoring as well as a broad literature review of many useful FDD approaches are presented.
Journal ArticleDOI

Probability-Relevant Incipient Fault Detection and Diagnosis Methodology With Applications to Electric Drive Systems

TL;DR: This brief will develop a new fault detection and diagnosis scheme called probability-relevant principal component analysis from the probability view point that is more sensitive to faults under an acceptable false alarm ratio and more accurate in diagnosing faults with the aid of improved fault detectability.
References
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Book

Matrix computations

Gene H. Golub
Book

Table of Integrals, Series, and Products

TL;DR: Combinations involving trigonometric and hyperbolic functions and power 5 Indefinite Integrals of Special Functions 6 Definite Integral Integral Functions 7.Associated Legendre Functions 8 Special Functions 9 Hypergeometric Functions 10 Vector Field Theory 11 Algebraic Inequalities 12 Integral Inequality 13 Matrices and related results 14 Determinants 15 Norms 16 Ordinary differential equations 17 Fourier, Laplace, and Mellin Transforms 18 The z-transform
Book

Matrix Analysis

TL;DR: In this article, the authors present results of both classic and recent matrix analyses using canonical forms as a unifying theme, and demonstrate their importance in a variety of applications, such as linear algebra and matrix theory.
Journal ArticleDOI

Principal components analysis corrects for stratification in genome-wide association studies

TL;DR: This work describes a method that enables explicit detection and correction of population stratification on a genome-wide scale and uses principal components analysis to explicitly model ancestry differences between cases and controls.
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