1,721,093 research outputs found
Nonlinear Methods for Fault Diagnosis
No full textThe model–based approach to fault diagnosis in technical processes has been
receiving more and more attention over the last four decades, in the contexts of both
research and real plant application.
Stemming from this activity, a great variety of methods are found in current
literature, based on the use of mathematical models of the technical process under
diagnosis and exploiting advanced control theory.
Model–based fault diagnosis methods usually use residuals which indicate changes
between the process and the model. One general assumption is that the residuals are
changed significantly so that a detection is possible. This means that the residual size
after the appearance of a fault is large and long enough to be detectable.
This chapter provides an overview on different fault diagnosis strategies, with
particular attention to the Fault Detection and Isolation (FDI) methods related to the
dynamic processes and the application examples considered in this book.
All the methods considered require that the technical process can be described
by a mathematical model. As there is almost never an exact agreement between the
model used to represent the process and the plant, the model–reality discrepancy is of
primary interest.
Hence, the most important issue in model–based fault detection is concerned with
the accuracy of the model describing the behaviour of the monitored system. This
issue has become a central research theme over recent years, as modelling uncertainty
arises from the impossibility of obtaining complete knowledge and understanding of
the monitored process.
The main focus of this chapter is the mathematical description aspects of the
process whose faults are to be detected and isolated. The chapter also studies the
general structure of the controlled system, its possible fault locations and modes.
Residual generation is then identified as an essential problem in model–based FDI,
since, if it is not performed correctly, some fault information could be lost. The general
framework for the residual generation is also recalled.
Residual generators based on different methods, such as input–output, state and
output observers, parity relations and parameter estimations, are just special cases
in this general framework. In the following, some commonly used residual generation
and evaluation techniques are discussed and their mathematical formulation presented.
Finally, the chapter presents and summarises special features and problems
regarding the different methods
Nonlinear Modeling for Fault‐tolerant Control
No full textAs already remarked, model–based and data–driven FDI strategies have been
studied for over 40 years, however they still represent an open research domain when
considered to be applied to dynamic processes, and many problems are waiting to be
solved. The material presented in this monograph has inevitably had to end before all
the interesting topics for future FDI research could be fully explored. In the
following sections the authors describe some important topics that should help the
reader to understand how to move from fault diagnosis to fault tolerance.
Moreover, this chapter presents the fault tolerant control algorithms applied to
dynamic processes. In general, they are based on the signal correction principle,
which means that the control system is not modified since the inputs and outputs of
the baseline controller are compensated according to the estimated faults. The fault
tolerant control algorithms recalled in this chapter rely on the fault diagnosis design
for nonlinear systems addressed in the monograph. Passive and active fault tolerant
control systems are also discussed and compared, in order to highlight the achievable
performances and the complexity of their design procedures. Controller
reconfiguration mechanisms are also considered, which are able to guarantee the
system stability and satisfactory performance
Diagnosis techniques for sensor faults of industrial processes
No full textIn this paper a model-based procedure exploitinganalytical redundancy for the detection and isolation of faults ininput--output control sensors of a dynamic system is presented.The diagnosis system is based on state estimators, namely dynamicobservers or Kalman filters designed in deterministic and stochasticenvironment respectively, and uses residual analysis and statisticaltests for fault detection and isolation.The state estimators are obtained from input--output data process andstandard identification techniques based on ARX orerrors--in--variables models, depending on signal to noise ratio. Inthe latter case the Kalman filter parameters, i.e. the modelparameters and the input--output noise variances, are obtained byprocessing the noisy data according to the Frisch scheme rules. The proposed fault detection and isolation tool has been tested on a single--shaft industrial gas turbine model. Results from simulation show that minimum detectable faults are perfectly compatible with the industrial target of this application
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
A new aerodynamic decoupled frequential FDIR methodology for satellite actuator faults
No full textThis paper presents new results regarding the development of a supervision scheme for a nonlinear satellite model. The main issue concerns the handling of frequency faults affecting the reaction wheels of a spacecraft attitude control system, that is, how to detect and isolate faults, how to determine the different frequencies characterising these faults through spectral analysis and lastly, how to prevent propagation into failures with potential mission abortion as a consequence. Thus, this work investigates the design of a scheme for fault detection, isolation and control reconfiguration applied to the reaction wheels of a spacecraft attitude control, based on the satellite model. This scheme is classifiable as active fault tolerant control. As the study focuses on a general satellite nonlinear model, where aerodynamic and gravitational disturbances, as well as measurement errors, are present, the robustness of the suggested strategy is achieved by exploiting an explicit disturbance decoupling method via a nonlinear geometric approach. To achieve accurate fault diagnosis, aerodynamic disturbance decoupling represents the key point because the aerodynamic model is often uncertain. Moreover, an improvement of the nonlinear geometric approach is presented, to realise both aerodynamic and manoeuvre decoupled fault diagnosis. To the best authors' knowledge, this is the first works presenting a methodology
for frequency fault diagnosis, which is based on the nonlinear geometric approach for fault and disturbance decoupling. The obtained results demonstrate that the proposed methodology can achieve better performances with respect to traditional fault detection and isolation
schemes
Foreword [to Robust and Fault-Tolerant Control. Neural-Network-Based Solutions]
No full textThis monograph aims at presenting some novel ideas, concepts and results in robust fault tolerant control. The rapid development of control technology has an impact on all areas of the control discipline: new theory, advanced control solutions, new industrial processes, computer methods and implementations, new applications, new philosophies, and new challenges. Much of this development work resides in industrial reports, feasibility study papers and reports of advanced collaborative projects. Therefore, this monograph offers an opportunity for researchers, practitioners and students to have an extended and clear exposition of new investigations in all aspects of robust fault tolerant control for wider and rapid dissemination.
As many technological systems become more complex, widespread and integrated, the effects of system faults can be simply devastating to the infrastructure of modem society. Feedback control is just one important component of total system supervision. Fault tolerant control represents further components with extensive commercial, industrial and societal implications if only we could work out how to do it in a robust and inexpensive manner. The model-based approach is the usual solution of the practical fault tolerant control design, but as the author Krzysztof Patan has highlighted in this monograph, neural network based methodologies can be successfully exploited. The search for reliable, robust and inexpensive fault tolerant control methods has been active since the early 1980s. Since 1991, the International Federation of Automatic Control (IFAC) has created the SAFEPROCESS Steering Committee to promote research, developments and applications in the fault tolerant control field. The last decade has seen the formalisation of several theoretical approaches accompanied by some attempts to standardise nomenclature in the field.
The related literature does not have many entries from this important research area, even if several monographs can represent interesting contributions on fault tolerant control, even if they use quite different ideas and principles. To these we can now add this monograph by Krzysztof Patan. Key features of this text include useful survey material, new approaches based on data-driven and neural network based methodologies, as well as application studies that help to understand advantages and drawbacks of the suggested strategies and tools. Different groups of readers ranging from industrial engineers wishing to gain insight into the applications potential of new fault tolerant control methods relying on artificial intelligence tools, to the academic control community looking for new problems to tackle will find much to learn from this monograph
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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