Book Image

Dynamic System Reliability

By : Liudong Xing, Gregory Levitin, Chaonan Wang
Book Image

Dynamic System Reliability

By: Liudong Xing, Gregory Levitin, Chaonan Wang

Overview of this book

This book focuses on hot issues of dynamic system reliability, systematically introducing the reliability modeling and analysis methods for systems with imperfect fault coverage, systems with function dependence, systems subject to deterministic or probabilistic common-cause failures, systems subject to deterministic or probabilistic competing failures, and dynamic standby sparing systems. It presents recent developments of such extensions involving reliability modeling theory, reliability evaluation methods, and features numerous case studies based on real-world examples. The presented dynamic reliability theory can enable a more accurate representation of actual complex system behavior, thus more effectively guiding the reliable design of real-world critical systems. The book begins by describing the evolution from the traditional static reliability theory to the dynamic system reliability theory and provides a detailed investigation of dynamic and dependent behaviors in subsequent chapters. Although written for those with a background in basic probability theory and stochastic processes, the book includes a chapter reviewing the fundamentals that readers need to know in order to understand the contents of other chapters that cover advanced topics in reliability theory and case studies.
Table of Contents (14 chapters)
Free Chapter
1 Introduction
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9.1 Overview

Chapter 8 focuses on reliability analysis of systems subject to deterministic competing failures, where the local failure (LF) of a trigger component, if it happens first, can cause a deterministic or certain isolation effect to propagated failure with global effect (PFGEs) originating from its corresponding dependent components within the same functional dependence (FDEP) group. However, in some real‐world systems, such an isolation effect can be probabilistic or uncertain.

For example, consider a relay‐assisted wireless sensor network (WSN) system where wireless signal attenuations can degrade the system performance significantly. Some sensors preferably deliver their sensed information to the sink device through a relay node [1]. Each component can undergo LFs (e.g. due to disabled transmissions) and PFGEs (e.g. due to jamming attacks). When the relay fails locally, each sensor may increase its transmission power to be wirelessly connected to the sink device...