A Review of Process Fault Detection and Diagnosis Part I : Quantitative Model-Based Methods
TL;DR: This three part series of papers is to provide a systematic and comparative study of various diagnostic methods from different perspectives and broadly classify fault diagnosis methods into three general categories and review them in three parts.
About: This article is published in Computers & Chemical Engineering.The article was published on 2003-03-15. It has received 2263 citations till now. The article focuses on the topics: Fault detection and isolation & Process (engineering).
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TL;DR: A bibliographical review on reconfigurable fault-tolerant control systems (FTCS) is presented, with emphasis on the reconfiguring/restructurable controller design techniques.
2,455 citations
TL;DR: The three-part survey paper aims to give a comprehensive review of real-time fault diagnosis and fault-tolerant control, with particular attention on the results reported in the last decade.
Abstract: With the continuous increase in complexity and expense of industrial systems, there is less tolerance for performance degradation, productivity decrease, and safety hazards, which greatly necessitates to detect and identify any kinds of potential abnormalities and faults as early as possible and implement real-time fault-tolerant operation for minimizing performance degradation and avoiding dangerous situations. During the last four decades, fruitful results have been reported about fault diagnosis and fault-tolerant control methods and their applications in a variety of engineering systems. The three-part survey paper aims to give a comprehensive review of real-time fault diagnosis and fault-tolerant control, with particular attention on the results reported in the last decade. In this paper, fault diagnosis approaches and their applications are comprehensively reviewed from model- and signal-based perspectives, respectively.
2,026 citations
Cites background from "A Review of Process Fault Detection..."
...per [10]–[12] on fault diagnosis was presented in 2003 from the viewpoint of quantitative mode-based, qualitative modelbased, and process history-based methods, respectively....
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TL;DR: Characteristics of the process industry data which are critical for the development of data-driven Soft Sensors are discussed.
1,399 citations
TL;DR: A basic data-driven design framework with necessary modifications under various industrial operating conditions is sketched, aiming to offer a reference for industrial process monitoring on large-scale industrial processes.
Abstract: Recently, to ensure the reliability and safety of modern large-scale industrial processes, data-driven methods have been receiving considerably increasing attention, particularly for the purpose of process monitoring. However, great challenges are also met under different real operating conditions by using the basic data-driven methods. In this paper, widely applied data-driven methodologies suggested in the literature for process monitoring and fault diagnosis are surveyed from the application point of view. The major task of this paper is to sketch a basic data-driven design framework with necessary modifications under various industrial operating conditions, aiming to offer a reference for industrial process monitoring on large-scale industrial processes.
1,289 citations
Cites background from "A Review of Process Fault Detection..."
...Papers dedicated to review and analyze the state of the art of the model-based process monitoring and fault diagnosis techniques can be found in [15]–[20]....
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TL;DR: A survey of the various model-based FDIR methods developed in the last decade is presented, and various techniques of implementing reconfigurable control strategy in response to faults are discussed.
Abstract: Fault detection, isolation, and reconfiguration (FDIR) is an important and challenging problem in many engineering applications and continues to be an active area of research in the control community. This paper presents a survey of the various model-based FDIR methods developed in the last decade. In the paper, the FDIR problem is divided into the fault detection and isolation (FDI) step, and the controller reconfiguration step. For FDI, we discuss various model-based techniques to generate residuals that are robust to noise, unknown disturbance, and model uncertainties, as well as various statistical techniques of testing the residuals for abrupt changes (or faults). We then discuss various techniques of implementing reconfigurable control strategy in response to faults.
1,217 citations
Cites methods from "A Review of Process Fault Detection..."
...[2]–[4] which focused on FDI methods and applications in process chemical engineering, and a survey paper by Angeli et al....
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References
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TL;DR: It is demonstrated that finite linear combinations of compositions of a fixed, univariate function and a set of affine functionals can uniformly approximate any continuous function ofn real variables with support in the unit hypercube.
Abstract: In this paper we demonstrate that finite linear combinations of compositions of a fixed, univariate function and a set of affine functionals can uniformly approximate any continuous function ofn real variables with support in the unit hypercube; only mild conditions are imposed on the univariate function. Our results settle an open question about representability in the class of single hidden layer neural networks. In particular, we show that arbitrary decision regions can be arbitrarily well approximated by continuous feedforward neural networks with only a single internal, hidden layer and any continuous sigmoidal nonlinearity. The paper discusses approximation properties of other possible types of nonlinearities that might be implemented by artificial neural networks.
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TL;DR: This paper is concerned with the construction of planes of closest fit to systems of points in space and the relationships between these planes and the planes themselves.
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01 Jan 1972
TL;DR: This completely revised second edition presents an introduction to statistical pattern recognition, which is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field.
Abstract: This completely revised second edition presents an introduction to statistical pattern recognition Pattern recognition in general covers a wide range of problems: it is applied to engineering problems, such as character readers and wave form analysis as well as to brain modeling in biology and psychology Statistical decision and estimation, which are the main subjects of this book, are regarded as fundamental to the study of pattern recognition This book is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field Each chapter contains computer projects as well as exercises
10,526 citations
TL;DR: In this paper, the problem of the estimation of a probability density function and of determining the mode of the probability function is discussed. Only estimates which are consistent and asymptotically normal are constructed.
Abstract: : Given a sequence of independent identically distributed random variables with a common probability density function, the problem of the estimation of a probability density function and of determining the mode of a probability function are discussed. Only estimates which are consistent and asymptotically normal are constructed. (Author)
10,114 citations
TL;DR: Principal Component Analysis is a multivariate exploratory analysis method useful to separate systematic variation from noise and to define a space of reduced dimensions that preserve noise.
8,660 citations