方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 基于风险的可靠性分析× | 基于风险的故障树分析× | |
|---|---|---|
| 领域 | 实验设计 | 实验设计 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1960s–1990s (risk-informed frameworks codified ~1980s–1990s) | 1961 (FTA origin); risk-based integration formalised 1975–1981 |
| 提出者≠ | Multiple contributors; formalized in reliability engineering literature from the 1960s onward (MIL-HDBK-217, IEC 60300 series) | H.A. Watson (Bell Labs) and developed further by Boeing/U.S. Air Force; risk-based extension via NRC probabilistic risk assessment programs |
| 类型≠ | Quantitative / semi-quantitative engineering analysis | Quantitative safety and reliability analysis |
| 开创性文献≠ | Modarres, M., Kaminskiy, M., & Krivtsov, V. (2006). Reliability Engineering and Risk Analysis: A Practical Guide (2nd ed.). CRC Press. ISBN: 978-0849392016 | Vesely, W. E., Goldberg, F. F., Roberts, N. H., & Haasl, D. F. (1981). Fault Tree Handbook. U.S. Nuclear Regulatory Commission, NUREG-0492. link ↗ |
| 别名 | RBRA, risk-informed reliability analysis, risk-based dependability analysis, probabilistic risk and reliability assessment | RB-FTA, risk-informed FTA, quantitative fault tree analysis, probabilistic fault tree analysis |
| 相关 | 6 | 6 |
| 摘要≠ | Risk-based reliability analysis (RBRA) is an engineering methodology that combines classical reliability analysis — quantifying failure rates, component lifetimes, and system dependability — with risk assessment frameworks that weigh the severity and consequences of each failure mode. By ranking failures according to both their likelihood and their impact, RBRA guides engineers in allocating inspection, maintenance, and redesign resources where they matter most, rather than treating all potential failures as equally important. | Risk-based fault tree analysis (RB-FTA) combines classical fault tree analysis with explicit quantitative risk assessment. Starting from an undesired top event, the analyst decomposes it into contributing causes using AND/OR logic gates, assigns failure probabilities to basic events from reliability databases or historical data, and then propagates those probabilities through the tree to compute top-event likelihood. The result is expressed as risk — probability weighted by consequence severity — enabling prioritisation of safety interventions by their actual risk reduction impact. |
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