作 者： Anatoly Lisnianski 著 出 版 社：
- 出版时间： 2003-12-1
- 字 数：
- 版 次： 1
- 页 数： 358
- 印刷时间：
- 开 本：
- 印 次： 1
- 纸 张：
- I S B N ： 9789812383068
- 包 装： 精装
定价：￥467.00
内容简介
Most books on reliability theory are devoted to traditional binary reliability models allowing for only two possible states for a system and its components: perfect functionality and complete failure. However, many real-world systems are composed of multi-state components, which have different performance levels and several failure modes with various effects on the entire system performance (degradation). Such systems are called Multi-State Systems (MSS). The examples of MSS are power systems where the component performance is characterized by the generating capacity, computer systems where the component performance is characterized by the data processing speed, communication systems, etc.
This book is the first to be devoted to Multi-State System (MSS) reliability analysis and optimization. It provides a historical overview of the field, presents basic concepts of MSS, defines MSS reliability measures, and systematically describes the tools for MSS reliability assessment and optimization. Basic methods for MSS reliability assessment, such as a Boolean methods extension, basic random process methods (both Markov and semi-Markov) and universal generating function models, are systematically studied. A universal genetic algorithm optimization technique and all details of its application are described. All the methods are illustrated by numerical examples. The book also contains many examples of application of reliability assessment and optimization methods to real engineering problems.
The aim of this book is to give a comprehensive, up-to-date presentation of MSS reliability theory based on modern advances in this field and provide a theoretical summary and examples of engineering applications to a variety of technical problems. From this point of view the book bridges the gap between theoretical advances and practical reliability engineering
目录
Preface
Introduction and brief historical overview
General notation and acronyms
Chapter 1. Basic concepts of Multi-State Systems
1.1. Multi-state systems: main definitions and properties
1.1.1. Generic MSS model
1.1.2. Main properties of MSS
1.1.2.1. Relevancy of the system elements
1.1.2.2. Coherency
1.1.2.3. Homogeneity
1.2. Multi-state system reliability and its measures
1.2.1. MSS acceptability function and reliability
1.2.2. Relevancy and coherency in MSS reliability context
1.2.3. MSS reliability indices
1.3. Types of MSS
1.3.1. MSS with typical simple configurations
1.3.1.1. Series structure
1.3.1.2. Parallel structure
1.3.1.3. Bridge structure
1.3.2. Systems with two failure modes
1.3.3. Weighted voting systems
1.3.4. Multi-state consecutively connected systems
1.3.5. Multi-state sliding window systems
1.3.6. Multi-state networks
1.3.6.1. Multi-state edges models
1.3.6.2. Multi-state vertices models
1.3.6.3. Mixed multi-state models
Exercises
References
Chapter 2. Extension of Boolean methods for MSS reliability analysis
2.1. Multi-valued structure function approach
2.1.1. Path and cut vectors
2.1.2. Multi-valued structure function
2.1.3. Evaluating the system reliability indices
2.1.4. Reliability bounding
2.2. Multi-state block diagrams and fault trees
2.2.1. Structure function representation using binary variables
2.2.2. MSS reliability block diagrams
2.2.3. MSS fault trees
2.2.4. Multi-valued logic trees and Boolean algebra with restrictions
2.2.4.1. Basic definitions of Boolean algebra with restrictions
2.2.4.2. Boolean reduction of multi-valued logic trees
2.2.4.3. Derivation of the complete base of prime implicants
Exercises
References
Chapter 3. Basic random processes methods for MSS reliability assessment
3.1. General concepts
3.2. Markov models
3.2.1. Main definitions and properties
3.2.2. Markov models for evaluating reliability of multi-state elements
3.2.2.1. Non-repairable multi-state elements
3.2.2.2. Repairable multi-state elements
3.2.2.3. Markov models for the multi-state element with variable demand
3.2.3. Markov models for evaluating the reliability of the multi-state system
3.3. Markov reward models
3.3.1. Basic definitions and model description
3.3.2. Computation of MSS reliability measures
3.3.2.1. Mean number of failures
3.3.2.2. Mean time to failure
……
Chapter 4 Universal Generating Function (UGF)models
Chapter 5 MSS reliability optimization
Chapter 6 Application Problems
Concluding remarks(further research)
Index
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