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Fault Diagnosis And Prognosis Techniques For Complex Engineering Systems

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Fault Diagnosis and Prognosis Techniques for Complex Engineering Systems

Fault Diagnosis and Prognosis Techniques for Complex Engineering Systems Book
Author : Hamid Reza Karimi
Publisher : Academic Press
Release : 2021-06-05
ISBN : 0128224886
Language : En, Es, Fr & De

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Book Description :

Fault Diagnosis and Prognosis Techniques for Complex Engineering Systems gives a systematic description of the many facets of envisaging, designing, implementing, and experimentally exploring emerging trends in fault diagnosis and failure prognosis in mechanical, electrical, hydraulic and biomedical systems. The book is devoted to the development of mathematical methodologies for fault diagnosis and isolation, fault tolerant control, and failure prognosis problems of engineering systems. Sections present new techniques in reliability modeling, reliability analysis, reliability design, fault and failure detection, signal processing, and fault tolerant control of engineering systems. Sections focus on the development of mathematical methodologies for diagnosis and prognosis of faults or failures, providing a unified platform for understanding and applicability of advanced diagnosis and prognosis methodologies for improving reliability purposes in both theory and practice, such as vehicles, manufacturing systems, circuits, flights, biomedical systems. This book will be a valuable resource for different groups of readers – mechanical engineers working on vehicle systems, electrical engineers working on rotary machinery systems, control engineers working on fault detection systems, mathematicians and physician working on complex dynamics, and many more. Presents recent advances of theory, technological aspects, and applications of advanced diagnosis and prognosis methodologies in engineering applications Provides a series of the latest results, including fault detection, isolation, fault tolerant control, failure prognosis of components, and more Gives numerical and simulation results in each chapter to reflect engineering practices

Bond Graphs for Modelling Control and Fault Diagnosis of Engineering Systems

Bond Graphs for Modelling  Control and Fault Diagnosis of Engineering Systems Book
Author : Wolfgang Borutzky
Publisher : Springer
Release : 2016-12-31
ISBN : 3319474340
Language : En, Es, Fr & De

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Book Description :

This book presents theory and latest application work in Bond Graph methodology with a focus on: • Hybrid dynamical system models, • Model-based fault diagnosis, model-based fault tolerant control, fault prognosis • and also addresses • Open thermodynamic systems with compressible fluid flow, • Distributed parameter models of mechanical subsystems. In addition, the book covers various applications of current interest ranging from motorised wheelchairs, in-vivo surgery robots, walking machines to wind-turbines.The up-to-date presentation has been made possible by experts who are active members of the worldwide bond graph modelling community. This book is the completely revised 2nd edition of the 2011 Springer compilation text titled Bond Graph Modelling of Engineering Systems – Theory, Applications and Software Support. It extends the presentation of theory and applications of graph methodology by new developments and latest research results. Like the first edition, this book addresses readers in academia as well as practitioners in industry and invites experts in related fields to consider the potential and the state-of-the-art of bond graph modelling.

Fault Diagnosis of Hybrid Dynamic and Complex Systems

Fault Diagnosis of Hybrid Dynamic and Complex Systems Book
Author : Moamar Sayed-Mouchaweh
Publisher : Springer
Release : 2018-03-27
ISBN : 3319740148
Language : En, Es, Fr & De

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Book Description :

Online fault diagnosis is crucial to ensure safe operation of complex dynamic systems in spite of faults affecting the system behaviors. Consequences of the occurrence of faults can be severe and result in human casualties, environmentally harmful emissions, high repair costs, and economical losses caused by unexpected stops in production lines. The majority of real systems are hybrid dynamic systems (HDS). In HDS, the dynamical behaviors evolve continuously with time according to the discrete mode (configuration) in which the system is. Consequently, fault diagnosis approaches must take into account both discrete and continuous dynamics as well as the interactions between them in order to perform correct fault diagnosis. This book presents recent and advanced approaches and techniques that address the complex problem of fault diagnosis of hybrid dynamic and complex systems using different model-based and data-driven approaches in different application domains (inductor motors, chemical process formed by tanks, reactors and valves, ignition engine, sewer networks, mobile robots, planetary rover prototype etc.). These approaches cover the different aspects of performing single/multiple online/offline parametric/discrete abrupt/tear and wear fault diagnosis in incremental/non-incremental manner, using different modeling tools (hybrid automata, hybrid Petri nets, hybrid bond graphs, extended Kalman filter etc.) for different classes of hybrid dynamic and complex systems.

Machine Learning and Knowledge Discovery for Engineering Systems Health Management

Machine Learning and Knowledge Discovery for Engineering Systems Health Management Book
Author : Ashok N. Srivastava,Jiawei Han
Publisher : CRC Press
Release : 2011-11-16
ISBN : 1439841780
Language : En, Es, Fr & De

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Book Description :

Machine Learning and Knowledge Discovery for Engineering Systems Health Management presents state-of-the-art tools and techniques for automatically detecting, diagnosing, and predicting the effects of adverse events in an engineered system. With contributions from many top authorities on the subject, this volume is the first to bring together the two areas of machine learning and systems health management. Divided into three parts, the book explains how the fundamental algorithms and methods of both physics-based and data-driven approaches effectively address systems health management. The first part of the text describes data-driven methods for anomaly detection, diagnosis, and prognosis of massive data streams and associated performance metrics. It also illustrates the analysis of text reports using novel machine learning approaches that help detect and discriminate between failure modes. The second part focuses on physics-based methods for diagnostics and prognostics, exploring how these methods adapt to observed data. It covers physics-based, data-driven, and hybrid approaches to studying damage propagation and prognostics in composite materials and solid rocket motors. The third part discusses the use of machine learning and physics-based approaches in distributed data centers, aircraft engines, and embedded real-time software systems. Reflecting the interdisciplinary nature of the field, this book shows how various machine learning and knowledge discovery techniques are used in the analysis of complex engineering systems. It emphasizes the importance of these techniques in managing the intricate interactions within and between the systems to maintain a high degree of reliability.

Diagnostic Techniques in Industrial Engineering

Diagnostic Techniques in Industrial Engineering Book
Author : Mangey Ram,J. Paulo Davim
Publisher : Springer
Release : 2017-10-20
ISBN : 3319654977
Language : En, Es, Fr & De

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Book Description :

This book presents the most important tools, techniques, strategy and diagnostic methods used in industrial engineering. The current widely accepted methods of diagnosis and their properties are discussed. Also, the possible fruitful areas for further research in the field are identified.

NASA Tech Briefs

NASA Tech Briefs Book
Author : Anonim
Publisher : Unknown
Release : 2007
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download NASA Tech Briefs book written by , available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Model based Health Monitoring of Hybrid Systems

Model based Health Monitoring of Hybrid Systems Book
Author : Danwei Wang,Ming Yu,Chang Boon Low,Shai Arogeti
Publisher : Springer Science & Business Media
Release : 2013-05-23
ISBN : 1461473691
Language : En, Es, Fr & De

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Book Description :

This book systematically presents a comprehensive framework and effective techniques for in-depth analysis, clear design procedure, and efficient implementation of diagnosis and prognosis algorithms for hybrid systems. It offers an overview of the fundamentals of diagnosis\prognosis and hybrid bond graph modeling. This book also describes hybrid bond graph-based quantitative fault detection, isolation and estimation. Moreover, it also presents strategies to track the system mode and predict the remaining useful life under multiple fault condition. A real world complex hybrid system—a vehicle steering control system—is studied using the developed fault diagnosis methods to show practical significance. Readers of this book will benefit from easy-to-understand fundamentals of bond graph models, concepts of health monitoring, fault diagnosis and failure prognosis, as well as hybrid systems. The reader will gain knowledge of fault detection and isolation in complex systems including those with hybrid nature, and will learn state-of-the-art developments in theory and technologies of fault diagnosis and failure prognosis for complex systems.

A Model Based Framework for Fault Diagnosis and Prognosis of Dynamical Systems with an Application to Helicopter Transmissions

A Model Based Framework for Fault Diagnosis and Prognosis of Dynamical Systems with an Application to Helicopter Transmissions Book
Author : Romano Patrick-Aldaco
Publisher : Unknown
Release : 2007
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

The thesis presents a framework for integrating models, simulation, and experimental data to diagnose incipient failure modes and prognosticate the remaining useful life of critical components, with an application to the main transmission of a helicopter. Although the helicopter example is used to illustrate the methodology presented, by appropriately adapting modules, the architecture can be applied to a variety of similar engineering systems. Models of the kind referenced are commonly referred to in the literature as physical or physics-based models. Such models utilize a mathematical description of some of the natural laws that govern system behaviors. The methodology presented considers separately the aspects of diagnosis and prognosis of engineering systems, but a similar generic framework is proposed for both. The methodology is tested and validated through comparison of results to data from experiments carried out on helicopters in operation and a test cell employing a prototypical helicopter gearbox. Two kinds of experiments have been used. The first one retrieved vibration data from several healthy and faulted aircraft transmissions in operation. The second is a seeded-fault damage-progression test providing gearbox vibration data and ground truth data of increasing crack lengths. For both kinds of experiments, vibration data were collected through a number of accelerometers mounted on the frame of the transmission gearbox. The applied architecture consists of modules with such key elements as the modeling of vibration signatures, extraction of descriptive vibratory features, finite element analysis of a gearbox component, and characterization of fracture progression. Contributions of the thesis include: (1) generic model-based fault diagnosis and failure prognosis methodologies, readily applicable to a dynamic large-scale mechanical system; (2) the characterization of the vibration signals of a class of complex rotary systems through model-based techniques; (3) a "reverse engineering" approach for fault identification using simulated vibration data; (4) the utilization of models of a faulted planetary gear transmission to classify descriptive system parameters either as fault-sensitive or fault-insensitive; and (5) guidelines for the integration of the model-based diagnosis and prognosis architectures into prognostic algorithms aimed at determining the remaining useful life of failing components.

Machine Learning and Knowledge Discovery for Engineering Systems Health Management

Machine Learning and Knowledge Discovery for Engineering Systems Health Management Book
Author : Ashok N. Srivastava,Jiawei Han
Publisher : CRC Press
Release : 2016-04-19
ISBN : 1439841799
Language : En, Es, Fr & De

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Book Description :

This volume presents state-of-the-art tools and techniques for automatically detecting, diagnosing, and predicting the effects of adverse events in an engineered system. It emphasizes the importance of these techniques in managing the intricate interactions within and between engineering systems to maintain a high degree of reliability. Reflecting the interdisciplinary nature of the field, the book explains how the fundamental algorithms and methods of both physics-based and data-driven approaches effectively address systems health management in application areas such as data centers, aircraft, and software systems.

Business Information Systems

Business Information Systems Book
Author : Witold Abramowicz,Adrian Paschke
Publisher : Springer
Release : 2018-07-11
ISBN : 3319939319
Language : En, Es, Fr & De

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Book Description :

This book constitutes the proceedings of the 21st International Conference on Business Information Systems, BIS 2018, held in Berlin, Germany, in July 2018. The BIS conference follows popular research trends, both in the academic and the business domain. Thus the theme of BIS 2018 was "Digital Transformation - An Imperative in Today's Business Markets". The 30 papers presented in this volume were carefully reviewed and selected from 96 submissions. They were organized in topical sections named: big and smart data and artificial intelligence; business and enterprise modeling; ICT project management; process management; smart infrastructures; social media and Web-based business information systems; applications, evaluations, and experiences.

Nuclear Power Plant Equipment Prognostics and Health Management Based on Data driven methods

Nuclear Power Plant Equipment Prognostics and Health Management Based on Data driven methods Book
Author : Jun Wang,Xianping Zhong,Xingang Zhao,Joseph P. Yurko,Shripad T. Revankar
Publisher : Frontiers Media SA
Release : 2021-09-13
ISBN : 2889712990
Language : En, Es, Fr & De

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Book Description :

Download Nuclear Power Plant Equipment Prognostics and Health Management Based on Data driven methods book written by Jun Wang,Xianping Zhong,Xingang Zhao,Joseph P. Yurko,Shripad T. Revankar, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Integrated System Health Management

Integrated System Health Management Book
Author : Jiuping Xu,Lei Xu
Publisher : Academic Press
Release : 2017-05-18
ISBN : 012813268X
Language : En, Es, Fr & De

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Book Description :

ISHM is an innovative combination of technologies and methods that offers solutions to the reliability problems caused by increased complexities in design, manufacture, use conditions, and maintenance. Its key strength is in the successful integration of reliability (quantitative estimation of successful operation or failure), "diagnosibility" (ability to determine the fault source), and maintainability (how to maintain the performance of a system in operation). It draws on engineering issues such as advanced sensor monitoring, redundancy management, probabilistic reliability theory, artificial intelligence for diagnostics and prognostics, and formal validation methods, but also "quasi-technical" techniques and disciplines such as quality assurance, systems architecture and engineering, knowledge capture, information fusion, testability and maintainability, and human factors. This groundbreaking book defines and explains this new discipline, providing frameworks and methodologies for implementation and further research. Each chapter includes experiments, numerical examples, simulations and case studies. It is the ideal guide to this crucial topic for professionals or researchers in aerospace systems, systems engineering, production engineering, and reliability engineering. Solves prognostic information selection and decision-level information fusion issues Presents integrated evaluation methodologies for complex aerospace system health conditions and software system reliability assessment Proposes a framework to perform fault diagnostics with a distributed intelligent agent system and a data mining approach for multistate systems Explains prognostic methods that combine both the qualitative system running state prognostics and the quantitative remaining useful life prediction

Advanced Maintenance Modelling for Asset Management

Advanced Maintenance Modelling for Asset Management Book
Author : Adolfo Crespo Márquez,Vicente González-Prida Díaz,Juan Francisco Gómez Fernández
Publisher : Springer
Release : 2017-07-12
ISBN : 3319580450
Language : En, Es, Fr & De

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Book Description :

This book promotes and describes the application of objective and effective decision making in asset management based on mathematical models and practical techniques that can be easily implemented in organizations. This comprehensive and timely publication will be an essential reference source, building on available literature in the field of asset management while laying the groundwork for further research breakthroughs in this field. The text provides the resources necessary for managers, technology developers, scientists and engineers to adopt and implement better decision making based on models and techniques that contribute to recognizing risks and uncertainties and, in general terms, to the important role of asset management to increase competitiveness in organizations.

Fault Diagnosis and Prognosis System for Aircraft

Fault Diagnosis and Prognosis System for Aircraft Book
Author : Zefeng Wang
Publisher : Unknown
Release : 2013
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

The goal of this thesis is to build an effective and practical intelligent system to diagnose and prognose aircraft faults. My research focuses on “The MOdeling, DIagnosis and PROgnosis (MODIPRO)” faults in complex systems. This work is a part of a project entitled FUI MODIPRO which is supported by Dassault Aviation. The objective of this project is to research and develop a software solution MODIPRO Version 0 and put it on the aviation market. This software solution can analyze a huge mass of data acquired from a flight and a fleet of aircraft, and the system can deduce rules for diagnosis and prognosis of faults. The system proposed in this thesis has been fully tested by using actual experimental data from a tri-engines system of aircrafts Z1, Z2 and Z3 (supplied by Dassault Aviation). The whole system would be built on a database containing about 67 hours of flight records involving 32 sensors. With the rapid development of modern aero technology and the market demand of high- performance, aircraft systems have become more and more. Thus, the classical diagnosis methods become less available. In the state of the art, unplanned maintenance takes place only at breakdowns, which is too late to observe the faults; the planned maintenance costs too much financial resources and manpower, which needs to set a periodic interval to perform preventive maintenance regardless of the health status of a physical asset. Although Build in Test (BIT) system is used widely, it also costs too much human and financial resource. In a general way the maintenance staffs need to connect the diagnostic box to the aircraft via interface after each flight mission. Because these classical methods often cause the false alarm, the planned maintenance is also indispensable today. In addition, classical diagnostic and prognostic system, such as Condition-Based Maintenance (CBM) and Prognostic Health Management (PHM), analyze the health state of aircrafts when they are on the ground - in the "offline" mode, they can't supervise the aircraft during the mission. In order to resolve these problems and guarantee a high ratio of attendance of aircraft, the system proposed in this thesis uses machine-learning methods to automatically detect, isolate, and even forecast aircraft faults while maintaining reliability and safety. The researches involve signals processing techniques, pattern recognition and classification. On the one hand, the diagnostic model allows the system to deduce the "real" cause of a fault by the observation and the treatment of acquired signals from flight records. On the other hand, the model can provide a progress of degradation of the health state and thus allows anticipating the faults or deferring the needless planned maintenance. The diagnosis system can locate and identify faults and the prognosis system can make the arbitration of a future maintenance plan on basis of the operating needs, the costs of rehabilitation, the risk of fault and the consequences. In addition to this, the system proposed in this thesis can be used not only in the off-line mode when aircraft maintenance occurs, but also in the on-line mode during the aircraft's mission. According to the different situations requirements, the missions of on-line system and off-line system are different. The on-line system is tasked with detecting faults and sending the alarms to the pilot and the Aircraft Ground Center (AGC) in time. The off-line system is obliged to locate the fault(s) and make a detail report to the maintenance center. Additionally, the system needs to analyze the flight data in the past time for the sake of forecasting the fault(s). In order to ensure the reliability of the system, different methods of machine learning are used in parallel as subsystems. These methods can compensate the disadvantages of each other. At first, the data are analyzed and pre-classified by Linear Analysis Discriminant (LDA), a classical and simple approach. On basis of the results, a novel approach of classification called SCM is proposed to improve the accuracy of diagnosis. SCM is different from SVM that requires the support vectors on the boundary of every class to distinguish the categories. SCM seeks the support vectors of true centers and sub-centers of each class during the machine learning. It can make the corresponding centers as the model of the class. The classification of data is simply done by the power distances of the centers. Furthermore, SCM can work for the prognosis analysis and perfectly deal with the nonlinear problem. The evolution of flight data is supervised by each fault model. On the basis of the evolution of the distances from the cloud of data to the centers, the system estimates the tendency of the evolution of data and forecast the probable faults in the future. Beyond a short-term prognosis of faults, the system can also be used to do a long-term evaluation of aircraft healthy state. This is more convincing and efficacious compared to regression methods and statistical methods, which lack the precision of a long-term regression and which require a longer time for data analysis. Although the diagnosis results of SCM and SVM are already satisfied with a correct detection rate that exceeds 95%, Artificial Neural Networks (ANN) are used to build another sub-system, so as to analyze the impact of using different types sensors on the different fault diagnosis and confirm the results from the models SVM and SCM. ANN is a quite different AI technic from SCM and SVM. It is a mathematical model that is inspired by the structure and functional aspects of biological neural networks. A neural network consists of an interconnected group of artificial neurons, and it processes information using a connectionist approach to computation. All the sensors are divided in to different groups corresponding to different types of the sensors. Different combinations of sensors are linked to the neural networks, thus we can study the importance of different types of aircraft sensors by the weights of networks and the diagnosis results of the faults. The methods, as SCM, SVM and ANN, need much time to accomplish machine learning, which cannot do the learning

Data Driven Technology for Engineering Systems Health Management

Data Driven Technology for Engineering Systems Health Management Book
Author : Gang Niu
Publisher : Springer
Release : 2016-07-27
ISBN : 9811020329
Language : En, Es, Fr & De

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Book Description :

This book introduces condition-based maintenance (CBM)/data-driven prognostics and health management (PHM) in detail, first explaining the PHM design approach from a systems engineering perspective, then summarizing and elaborating on the data-driven methodology for feature construction, as well as feature-based fault diagnosis and prognosis. The book includes a wealth of illustrations and tables to help explain the algorithms, as well as practical examples showing how to use this tool to solve situations for which analytic solutions are poorly suited. It equips readers to apply the concepts discussed in order to analyze and solve a variety of problems in PHM system design, feature construction, fault diagnosis and prognosis.

Reliability Risk and Safety Three Volume Set

Reliability  Risk  and Safety  Three Volume Set Book
Author : Radim Bris,Carlos Guedes Soares,Sebastián Martorell
Publisher : CRC Press
Release : 2009-08-20
ISBN : 0203859758
Language : En, Es, Fr & De

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Book Description :

Containing papers presented at the 18th European Safety and Reliability Conference (Esrel 2009) in Prague, Czech Republic, September 2009, Reliability, Risk and Safety Theory and Applications will be of interest for academics and professionals working in a wide range of industrial and governmental sectors, including Aeronautics and Aerospace, Aut

Simulation Methods for Reliability and Availability of Complex Systems

Simulation Methods for Reliability and Availability of Complex Systems Book
Author : Javier Faulin,Angel A. Juan,Sebastián Salvador Martorell Alsina,Jose Emmanuel Ramirez-Marquez
Publisher : Springer Science & Business Media
Release : 2010-04-22
ISBN : 1848822138
Language : En, Es, Fr & De

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Book Description :

Simulation Methods for Reliability and Availability of Complex Systems discusses the use of computer simulation-based techniques and algorithms to determine reliability and availability (R and A) levels in complex systems. The book: shares theoretical or applied models and decision support systems that make use of simulation to estimate and to improve system R and A levels, forecasts emerging technologies and trends in the use of computer simulation for R and A and proposes hybrid approaches to the development of efficient methodologies designed to solve R and A-related problems in real-life systems. Dealing with practical issues, Simulation Methods for Reliability and Availability of Complex Systems is designed to support managers and system engineers in the improvement of R and A, as well as providing a thorough exploration of the techniques and algorithms available for researchers, and for advanced undergraduate and postgraduate students.

Uncertainty in Complex Networked Systems

Uncertainty in Complex Networked Systems Book
Author : Tamer Başar
Publisher : Springer
Release : 2018-12-14
ISBN : 3030046303
Language : En, Es, Fr & De

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Book Description :

The chapters in this volume, and the volume itself, celebrate the life and research of Roberto Tempo, a leader in the study of complex networked systems, their analysis and control under uncertainty, and robust designs. Contributors include authorities on uncertainty in systems, robustness, networked and network systems, social networks, distributed and randomized algorithms, and multi-agent systems—all fields that Roberto Tempo made vital contributions to. Additionally, at least one author of each chapter was a research collaborator of Roberto Tempo’s. This volume is structured in three parts. The first covers robustness and includes topics like time-invariant uncertainties, robust static output feedback design, and the uncertainty quartet. The second part is focused on randomization and probabilistic methods, which covers topics such as compressive sensing, and stochastic optimization. Finally, the third part deals with distributed systems and algorithms, and explores matters involving mathematical sociology, fault diagnoses, and PageRank computation. Each chapter presents exposition, provides new results, and identifies fruitful future directions in research. This book will serve as a valuable reference volume to researchers interested in uncertainty, complexity, robustness, optimization, algorithms, and networked systems.

Advances in Engineering Design and Optimization III

Advances in Engineering Design and Optimization III Book
Author : Guo Fu Li,Valery Ya. Shchukin
Publisher : Trans Tech Publications Ltd
Release : 2012-10-26
ISBN : 3038138983
Language : En, Es, Fr & De

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Book Description :

These are the proceedings of the third International Conference on Engineering Design and Optimization (ICEDO 2012), held on May 25-27th 2012 in Shaoxing (P.R. China). Volume is indexed by Thomson Reuters CPCI-S (WoS). The 278 peer-reviewed papers are grouped into 4 chapters: Engineering Design - Theory and Practice; Product Design and Development; Manufacturing Systems Modeling and Optimization; Advanced Machining and Materials Processing Technology

Fault Detection Supervision and Safety of Technical Processes 2003 SAFEPROCESS 2003

Fault Detection  Supervision and Safety of Technical Processes 2003  SAFEPROCESS 2003  Book
Author : Marcel Staroswiecki,Eva Wu
Publisher : Elsevier
Release : 2004-03-12
ISBN : 9780080440118
Language : En, Es, Fr & De

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Book Description :

A three-volume work bringing together papers presented at 'SAFEPROCESS 2003', including four plenary papers on statistical, physical-model-based and logical-model-based approaches to fault detection and diagnosis, as well as 178 regular papers.