《空间故障树理论与系统可靠性分析（英文版）》（崔铁军，李莎莎）-图书推荐
内容提要
This book discusses the theory of the space fault tree framework, which is primarily used internationally for system reliability analysis. Through the integration of the factor space theory and the theory and method of intelligence, space fault tree can be used in intelligent analysis and big data processing. This book focuses on continuous space fault tree, discrete space fault tree, inward analysis of system factor structure, function structure analysis, system reliability with respect to influencing factors, cloudization space fault tree, cloud similarity, and clustering analysis and similarity.
目录
ContentsContent SummaryIntroductionChapter 1Introduction11.1Purpose and Significance11.2Summary of Research and Problems21.2.1Fault Tree Research21.2.2Multi-Factor Influence and Fault Big Data31.2.3System Function Structure Analysis and Factor Space1.2.4System Reliability and Influencing Factors1.2.5loud Model and Similarity81.2.6Object Calassification and Similarity111.3Deficiency of System Reliability121.4Main Research Content14References16Chapter 2Continuous Space Fault Tree232.1Concepts of CSFT242.2Fault Probability Distribution262.2.1Component Fault Probability Distribution262.2.2System Fault Probability Distribution282.3Importance Distributions352.3.1Probability Importance Distribution352.3.2Criticality Importance Distribution372.4System Fault Probability Distribution Trend502.5Calculation of MTLα502.6Conclusions53References59Chapter 3Discrete Space Fault Tree613.1Discrete Space Fault Tree613.2Significance of DSFT Modifed Using Fuzzy Structured Element653.3Factor Projection Fitting Metho663.4Constructions and Applications of EDSFT693.4.1E-Characteristic Function693.4.2E-Component Fault Probability Distribution733.4.3E-System Fault Probability Distribution743.4.4E-Probability Importance Distribution743.4.5E-Criticality Importance Distribution753.4.6E-System Fault Probability Distribution Trend753.4.7E-Component Domain Importance763.4.8E-Factor Importance Distribution783.4.9EFactor Joint Importance Distribution793.5Conclusions79References80Chapter 4Inward Analysis of System Factor Structure834.1Inward Analysis of System Factor Structure844.2Human-Machine Cognition864.3Table Method874.4Classification Reasoning Method884.5Mathematical Description of Cassification Reasoning Method934.6Item-By-Item Analyses944.7Mathematical Description of Item- By-Item Analyses954.8Conclusions98References99Chapter 5Function Structure Analysis and Factor Space1015.1Factor Analysis Method of Function Structue1035.1.1Factors and Dimension Variabitity1035.1.2Function Structure Analysis Space1045.2Factor Logic Description of Function Structure1055.2.1Axiom System of Function Structure Analyis1055.2.2Minimization Method of System Function Structure1095.3Analysis of System Function Structure1105.3.1Analysis with Incomplete Information1115.3.2Analysis with Complete Information113Reference117Chapter 6System Reliability with Influencing Factors1196.1Methodology of Concepts and Definition1216.2Analysis of Relationship between Reliability and Infuencing Factors1246.2.1Random Variable Decomposition Fomula1246.2.2Causal Relationship Reasoning1266.2.3Causal Concept Extraction1276.2.4Background Relationship Analysis1276.2.5Factor Dimension Reduction1286.2.6Compression of Fault Probability Distribution1306.3Algorithm Applation1326.3.1Random Variable Decomposition Formula1326.3.2Causal Relationship Reasoning1366.3.3Causal Concept Extraction1446.3.4Background Relationship Analysi1476.3.5Factor Dimension Reduction1506.3.6Cormpression of Fault Probability Distribution1536.4Conclusions156References158Chapter 7Cloudiation Space Fault Tee1617.1Definitions of SFT1637.2Construction of Cloudization Space Fault Tree16372.1Basis of CLSFT1637.2.2Cloudization Fauit Pobability Distribution1647.2.3Cloudization Fauit Pobability Distribution Trend1657.2.4Cloudization Importance Distribution Probability and Criticality1657.2.5Cloudization Factor Importance and Joint Importance Distribution1667.2.6Cloudization Component Domain Importance1677.2.7Cloudization Path Set Domain and Cut Set Domain1687.2.8Uncertainty Analysis of Rlibility Data1687.3Example Analysis1697.3.1Cloudization Fault Probability Distribution1707.3.2Cloudization Fault Probability Distribution Trend1727.3.3Cloudization Importance Distribution Probability and Criticality1787.3.4Cloudization Importance Distribution of Factor and Factor Joint1817.3.5Cloudization Component Domain Importance1857.3.6Cloudization Path Set Domain and Cut Set Domain18773.7Uncertainty Analysis of Reliability Data1877.4Conclusions196References196Chapter 8Cloud Similarity1998.1Similarity Algorithms of Cloud Model1998.2Cloud Similarity Computation Based on Envelope2018.3Algorithm Application2038.4Analyses of Algorithm Advantage2058.5Conclusions206References206Chapter 9Clustering Analysis and Similarity2079.1Preliminary K nowledge2079.2Concepts and Properties of Attribute Circle
精彩试读
Chapter 1 Introduction1.1 Purpose and SignificanceSystem reliability theory is one of the basic theories of safety science. Derived from system engineering， system reliability is mainly concerned with the possibility of system faults and accidents. Owing to improvements in modern science and indus-trialisation， to pursue greater economic and strategic goals， some countries have intensified their research and established large or super-large systems to meet their requirements. However， it was found that a decline in reliability occurs during the operation of a system with an increase in system complexity. In this case， the original problem is that the lessons learned after an accident cannot meet the requirements of the present system safety. Because the research method of the problem is primarily applicable to a low value of system， with low system reliability and no critical con-sequences of a fault， such a research approach is not significant for today"s large-scale and extremely complex systems. Therefore， during the 1950s， Britain and the US first proposed the concept of safety system engineering. At this time， some concepts of system engineering were introduced into the field of safety， particularly a reliability analysis method， and applied in the miltary and aerospace fields. Safety system engineering is， therefore， one of the basic aspects of safety science.Safety system engineering and system reliability analyses have since been developed under the conditions of relatively simple and low complexity systems and limited data scales. However， with the development of big data technology， in telli-gent science， system science， and related mathematical theories， existing system reliability analysis methods have also exposed certain problems， such as big data processing; reliability causation， stability， and reverse engineering; and the description of reliability changes. At the same time， existing system reliability analysis methods are mostly targeted at specific systems. Although such an analysis is effective， there has been a lack of abstraction at the system level， making it difficult to meet the required universality， scalability and adaptability. Therefore， the system reliability analysis method that achieves the above capabilities and meets future technological requirements is needed. It is， therefore， necessary to combine the system reliability analysis with intelligent science and big data technology.Space fault tree theory (SFT) [1] is a systerm reliability analysis method proposed by the authors in 2012. After some years of development， the preliminarily foun-dation of the SFT theory framework has been completed， which can satisfy the reliability analysis of a simple system， including big data processing， reliability causality， reliability stability， reliability reverse engineering， and a reliability change description，and achieves high universality， extensibility， and adaptability. Its development process integrates intelligent science and big data processing technology， including factor space theory [2]， fuzzy structured element theory [3]， and cloud model theory [4]， among others. Although some problems remain， the SFT still has adequate room to solve these issues through further development. We hope this book will broaden the basic research field of safety science， enabling readers to better understand SFT theory， factor space theory， and their role in the system reliability analysis， soeking a thoretical development of reliability adapted to intelligent science and big data technology. 1.2 Summary of Research and Problems1.2.1 Fault Tree ResearchThe fault tree is an important aspect of safety system engineering and plays a crucial role in the analysis of system safety and reliability in several industries. It has been widely used and studied around the world as a systermatic scientific method. The applications of the fault tree and studies conducted in different fields are reviewed in the following chapter. In medical research， the fault tree has been applied to the control of hand， foot， and mouth diseases [5]. For the safety of a laboratory-scale bioreactor， the fault tree analysis method was used to deal with hydrogen sulphide biotreatment [6]. In research into uncertainty， the problem was studied using fault tree [7. In addition， the decision tree method has been used to represent uncertainty based on proba-bility [8]. An uncertainty analysis of fault tree model based on basic events was also developed [9]. In addition， uncertainty in fault tree analysis was processed using a hybrid probabilistic-possibilistic framework [10]. In a study on system reliability analysis， a real-time systern analysis method based on fault tree was proposed [11]. A study on a non-repairable system was also conducted using dynamic fault tree and priority AND gates [12]. In an analysis of system safety， an extended fault tree was used to analyse the