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Methods systems and apparatus for analyzing complex systems via prognostic reasoning

机译:通过预后推理分析复杂系统的方法系统和装置

摘要

Methods and apparatus are provided for analyzing a complex system that includes a number of subsystems. Each subsystem comprises at least one sensor designed to generate sensor data. Sensor data from at least one of the sensors is processed to generate binary evidence of a sensed event, and complex evidence of a sensed event. The complex evidence has more sophisticated mathematical properties than the binary evidence. The complex evidence comprises one or more of: a condition indicator (CI), a health indicator (HI), and a prognostic indicator (PI). A system fault model (SFM) is provided that defines statistical relationships between binary evidence, complex evidence, and an underlying failure mode (FM) that is occurring in the complex system. The binary evidence and the complex evidence are processed to identify failure modes taking place within one or more of the subsystems. Based on the binary evidence and the complex evidence and the SFM, diagnostic conclusions can be generated regarding adverse events that are taking place within the complex system, and prognostic conclusions can be generated regarding adverse events that are predicted to take place within the complex system.
机译:提供了用于分析包括多个子系统的复杂系统的方法和装置。每个子系统包括至少一个被设计为生成传感器数据的传感器。来自至少一个传感器的传感器数据被处理以生成感测到的事件的二进制证据以及感测到的事件的复杂证据。复杂证据比二元证据具有更复杂的数学性质。复杂的证据包括以下一项或多项:状态指标(CI),健康指标(HI)和预后指标(PI)。提供了系统故障模型(SFM),该模型定义了二进制证据,复杂证据和复杂系统中发生的基础故障模式(FM)之间的统计关系。对二元证据和复杂证据进行处理以识别在一个或多个子系统内发生的故障模式。基于二元证据,复杂证据和SFM,可以生成有关复杂系统内发生的不良事件的诊断结论,可以生成有关预计发生在复杂系统内的不良事件的预后结论。

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