Hierarchical Probability Model Generation for Complex System Availability
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Solution Overview
Problem
Current methods for analyzing the reliability and availability of complex systems using fault trees and state space models face challenges in efficiently generating hierarchical probability models, leading to performance and reliability issues due to dependence between basic events and the complexity of large systems.
Innovation Solution
A hierarchical probability model generation system that includes an independent event analysis unit, event tree generation unit, and state transition model generation unit to specify independent events, generate event trees, and calculate occurrence probabilities, thereby improving the efficiency and reliability of availability analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a state space model is used to correctly analyze system availability considering dependence between basic events, then the reliability of availability analysis is improved, but the device complexity increases due to state explosion in large and complex systems
Solution Approach 1:
The patent divides the system into multiple subsystems, each with its own state space model. By segmenting the large system into smaller manageable parts, the state explosion problem is avoided while still capturing dependence relationships within each subsystem. The top event probability is then calculated by combining results from these segmented subsystems.
Solution Approach 2:
The patent introduces a hierarchical dimension to the analysis by creating a two-level structure: subsystem-level state space models and system-level fault tree analysis. This dimensional change allows the model to handle dependence relationships without requiring a single monolithic state space model of the entire system.
2Ease of operation
If automatic generation of fault tree and state space model is employed for complex systems, then the ease of operation is improved, but the productivity decreases due to inefficiency in model generation
Solution Approach 1:
The patent performs preliminary identification of basic events and their dependence relationships before generating the full models. By pre-analyzing the system configuration and availability requirements, the method prepares the necessary information structure in advance, making the subsequent automatic model generation more efficient and targeted.
Solution Approach 2:
The patent applies different modeling approaches to different parts of the system based on local characteristics. Subsystems with dependence relationships use state space models, while other parts use traditional fault tree analysis. This localized application of modeling techniques improves overall generation efficiency while maintaining accuracy where needed.
Data Source
AI summary
A hierarchical probability model capable of improving the performance and reliability of an availability analysis in a large and complex system is efficiently generated.A hierarchical probability model generation system includes: an independent event analysis unit that specifies independent events about operating conditions of a system on the basis of availability requirements of the system and configuration information of the system, the independent events being calculable independently of each other; an event tree generation unit that generates an event tree using the independent events; and a state transition model generation unit that generates state transition models used to calculate occurrence probabilities of the independent events.