Author: Mohammad Abdel Kareem Rasheed Jaradat
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
In this study, an efficient new hybrid approach for multiple sensors data fusion and fault detection is presented, addressing the problem with possible multiple faults, which is based on conventional fuzzy soft clustering and artificial immune system (AIS). The proposed hybrid system approach consists of three main phases. In the first phasesignal separation is performed using the Fuzzy C-Means (FCM) algorithm. Subsequently a single (fused) signal based on the information provided from the sensor signals is generated by the fusion engine. The information provided from the previous two phases is used for fault detection in the third phase based on the Artificial Immune System (AIS) negative selection mechanism. The simulations and experiments for multiple sensor systems have confirmed the strength of the new approach for online fusing and fault detection. The hybrid system gives a fault tolerance by handling different problems such as noisy sensor signals and multiple faulty sensors. This makes the new hybrid approach attractive for solving such fusion problems and fault detection during real time operations. This hybrid system is extended for early fault detection in complex mechanical systems based on a set of extracted features; these features characterize the collected sensors data. The hybrid system is able to detect the onset of fault conditions which can lead to critical damage or failure. This early detection of failure signs can provide more effective information for any maintenance actions or corrective procedure decisions.
Author: Debashis De
Publisher: Springer Nature
ISBN: 9811521255
Category : Technology & Engineering
Languages : en
Pages : 346
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Book Description
This book presents nature inspired computing applications for the wireless sensor network (WSN). Although the use of WSN is increasing rapidly, it has a number of limitations in the context of battery issue, distraction, low communication speed, and security. This means there is a need for innovative intelligent algorithms to address these issues.The book is divided into three sections and also includes an introductory chapter providing an overview of WSN and its various applications and algorithms as well as the associated challenges. Section 1 describes bio-inspired optimization algorithms, such as genetic algorithms (GA), artificial neural networks (ANN) and artificial immune systems (AIS) in the contexts of fault analysis and diagnosis, and traffic management. Section 2 highlights swarm optimization techniques, such as African buffalo optimization (ABO), particle swarm optimization (PSO), and modified swarm intelligence technique for solving the problems of routing, network parameters optimization, and energy estimation. Lastly, Section 3 explores multi-objective optimization techniques using GA, PSO, ANN, teaching–learning-based optimization (TLBO), and combinations of the algorithms presented. As such, the book provides efficient and optimal solutions for WSN problems based on nature-inspired algorithms.
Author:
Publisher:
ISBN:
Category :
Languages : pt-BR
Pages :
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Book Description
Este trabalho investiga métodos de detecção de falhas baseados em sistemasimunológicos artificiais, especificamente aqueles baseados no algoritmo deseleção negativa (NSA) e em outras técnicas de reconhecimento próprio/nãopróprio. Inicialmente, foi proposto um esquema de representação baseado emhiperesferas com centros e raios variáveis e três modelos capazes de gerardetectores, com esta representação, de forma eficiente. O primeiro modelo utilizaalgoritmos genéticos onde cada gene do cromossomo contém um índice para umponto de uma distribuição quasi-aleatória que servirá como centro do detector euma função decodificadora responsável por determinar os raios apropriados. Aaptidão do cromossomo é dada por uma estimativa do volume coberto atravésuma integral de Monte Carlo. O segundo modelo utiliza o particionamentoQuadtree para gerar o posicionamento dos detectores e o valor dos raios. Estemodelo pode realizar o particionamento a partir de uma função de detecção ouatravés de divisões recursivas de um detector inicial que ocupa todo o espaço. Oterceiro modelo é inspirado nas redes imunológicas. Neste modelo, as células Brepresentam os detectores e a rede formada por eles dá a posição e o raio de cadadetector. Experimentos com dados sintéticos e reais demonstram a capacidade dosalgoritmos propostos e que eles apresentam melhorias nos aspectos deescalabilidade e desempenho na detecção de falhas.
Author: Lee Suk-han
Publisher: Springer Science & Business Media
ISBN: 354089859X
Category : Technology & Engineering
Languages : en
Pages : 476
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Book Description
The ?eld of multi-sensor fusion and integration is growing into signi?cance as our societyisintransitionintoubiquitouscomputingenvironmentswithroboticservices everywhere under ambient intelligence. What surround us are to be the networks of sensors and actuators that monitor our environment, health, security and safety, as well as the service robots, intelligent vehicles, and autonomous systems of ever heightened autonomy and dependability with integrated heterogeneous sensors and actuators. The ?eld of multi-sensor fusion and integration plays key role for m- ing the above transition possible by providing fundamental theories and tools for implementation. This volume is an edition of the papers selected from the 7th IEEE International Conference on Multi-Sensor Integration and Fusion, IEEE MFI‘08, held in Seoul, Korea, August 20–22, 2008. Only 32 papers out of the 122 papers accepted for IEEE MFI’08 were chosen and requested for revision and extension to be included in this volume. The 32 contributions to this volume are organized into three parts: Part I is dedicated to the Theories in Data and Information Fusion, Part II to the Multi-Sensor Fusion and Integration in Robotics and Vision, and Part III to the Applications to Sensor Networks and Ubiquitous Computing Environments. To help readers understand better, a part summary is included in each part as an introduction. The summaries of Parts I, II, and III are prepared respectively by Prof. Hanseok Ko, Prof. Sukhan Lee and Prof. Hernsoo Hahn.
Author: Nader Meskin
Publisher: Springer Science & Business Media
ISBN: 1441983937
Category : Technology & Engineering
Languages : en
Pages : 176
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Book Description
“Fault Detection and Isolation: Multi-Vehicle Unmanned System” deals with the design and development of fault detection and isolation algorithms for unmanned vehicles such as spacecraft, aerial drones and other related vehicles. Addressing fault detection and isolation is a key step towards designing autonomous, fault-tolerant cooperative control of networks of unmanned systems. This book proposes a solution based on a geometric approach, and presents new theoretical findings for fault detection and isolation in Markovian jump systems. Also discussed are the effects of large environmental disturbances, as well as communication channels, on unmanned systems. The book proposes novel solutions to difficulties like robustness issues, as well as communication channel anomalies. “Fault Detection and Isolation: Multi-Vehicle Unmanned System” is an ideal book for researchers and engineers working in the fields of fault detection, as well as networks of unmanned vehicles.
Author: Lei Song
Publisher:
ISBN:
Category :
Languages : en
Pages : 172
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Book Description
Author:
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 980
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Book Description
Author: Santoshinee Mohapatra
Publisher:
ISBN: 9781805258902
Category : Computers
Languages : en
Pages : 0
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Book Description
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Author: Le Xu
Publisher:
ISBN: 9781109855845
Category :
Languages : en
Pages : 154
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Book Description
In this work, logistic regression and artificial neural network are firstly compared on their capability in fault diagnosis; then an existing fuzzy classification algorithm is extended to E-algorithm to alleviate the effect of data imbalance; afterwards, the immune system based Artificial Immune Recognition System (AIRS) algorithm is investigated for its capability in fault diagnosis using real-world data; lastly, a hybrid algorithm based on E-algorithm and AIRS is proposed to embed the rule extraction capability while performing satisfactory fault cause identification.
Author: Pawel Sniatala
Publisher: Springer
ISBN: 9783030331344
Category : Technology & Engineering
Languages : en
Pages : 202
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Book Description
This book provides a comprehensive analysis of Brooks-Iyengar Distributed Sensing Algorithm, which brings together the power of Byzantine Agreement and sensor fusion in building a fault-tolerant distributed sensor network. The authors analyze its long-term impacts, advances, and future prospects. The book starts by discussing the Brooks-Iyengar algorithm, which has made significant impact since its initial publication in 1996. The authors show how the technique has been applied in many domains such as software reliability, distributed systems and OS development, etc. The book exemplifies how the algorithm has enhanced new real-time features by adding fault-tolerant capabilities for many applications. The authors posit that the Brooks-Iyengar Algorithm will to continue to be used where fault-tolerant solutions are needed in redundancy system scenarios. This book celebrates S.S. Iyengar's accomplishments that led to his 2019 Institute of Electrical and Electronics Engineers' (IEEE) Cybermatics Congress "Test of Time Award" for his work on creating Brooks-Iyengar Algorithm and its impact in advancing modern computing.
