首页> 外文会议>Proceedings of the 2010 summer simulation multiconference book 3: Grand challenges in modeling amp; simulation symposium >Immune Systems Inspired Approach to Anomaly Detection, Fault Localization and Diagnosis in Complex Dynamic Systems
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Immune Systems Inspired Approach to Anomaly Detection, Fault Localization and Diagnosis in Complex Dynamic Systems

机译:免疫系统启发式的复杂动态系统异常检测,故障定位和诊断方法

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Almost prevalent use of electronics, complicated software, new materials, and technologies makes fault diagnosis and management in contemporary engineering systems increasingly difficult to deal with. Unavoidable design defects, quality variations in the production process, as well as different usage patterns, make it infeasible to foresee all possible faults that may occur on a given system. As a result, traditional precedent-based diagnostic approaches offer a very limited diagnostic coverage based on testing only for the a priori known or anticipated failures, often falsely presuming that the system is operating normally if the full set of diagnostic tests pass. To circumvent these difficulties and provide a more complete coverage for detection and localization of the source of any fault, a new paradigm for design of diagnostic systems is needed. An approach inspired by the functionalities and characteristics of natural immune systems is presented and discussed here. The capability of the newly proposed paradigm to isolate the source of an anomaly without the need to train with signatures characterizing the underlying fault is demonstrated in the simulations of a diesel engine Exhaust Gas Recirculation (EGR) system and a generator portion of a commercially available marine diesel-generator system.
机译:电子设备,复杂软件,新材料和技术的几乎普遍使用使当代工程系统中的故障诊断和管理变得越来越难以处理。不可避免的设计缺陷,生产过程中的质量变化以及不同的使用模式,使得无法预见给定系统上可能发生的所有可能的故障。结果,传统的基于先例的诊断方法仅基于对先验已知或预期的故障进行测试而提供非常有限的诊断范围,如果通过全部诊断测试,通常会错误地假定系统在正常运行。为了避免这些困难并提供更完整的覆盖范围以检测和定位任何故障源,需要一种新的诊断系统设计范式。本文介绍并讨论了一种受天然免疫系统功能和特性启发的方法。柴油发动机废气再循环(EGR)系统和市售船用发电机部分的仿真显示了新提出的范式能够隔离异常源,而无需进行具有潜在故障特征的训练的能力。柴油发电机系统。

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