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首页> 外文期刊>IEE Proceedings. Part D >Dynamic systems reliability evaluation using uncertainty techniques for performance monitoring
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Dynamic systems reliability evaluation using uncertainty techniques for performance monitoring

机译：使用不确定性技术对系统进行动态系统可靠性评估

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The authors suggest the use of fuzzy measures and fuzzy integrals in evaluating the reliability of control systems by approximating an experts view on a complex system when assessing the performance. The class of systems considered have structural complexity exhibiting a closed- form model of the underlying process. The approach may be described in three parts where in the first stage a rule-based classifier (‘spy') extracts ‘states of performance' from the process. It is shown that the rule-premise resembles a possibility based control chart and that the possibilistic version, embedded in a rule-based system, offers a comprehensive man--process interface while having a similar or slightly improved speed of detection. The reliability can be quantified based on a finite set of abstract states over which a certainty measure is defined. A prediction for a specified reliability interval of time is done by using a qualitative model akin to Markov stochastic processes and consequently decisions are made to alter the system structure. This framework allows distinct classes of uncertainty to be considered.
机译：作者建议通过在评估性能时近似专家对复杂系统的观点来使用模糊测度和模糊积分来评估控制系统的可靠性。所考虑的系统类别具有结构复杂性，展现出基础过程的封闭形式模型。可以在三个部分中描述该方法，其中在第一步中，基于规则的分类器（spy）从流程中提取“性能状态”。结果表明，规则前提类似于基于可能性的控制图，嵌入在基于规则的系统中的可能性版本提供了全面的人机界面，同时具有相似或略微提高的检测速度。可以基于有限的抽象状态集（在其上确定确定性度量）来量化可靠性。通过使用类似于Markov随机过程的定性模型，可以对指定的可靠性时间间隔进行预测，并据此做出更改系统结构的决策。该框架允许考虑不同类别的不确定性。

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