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Anomaly detection for a vibrating structure: A subspace identification/tracking approach

机译:异常检测振动结构:子空间识别/跟踪方法

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摘要

Mechanical devices operating in noisy environments lead to low signal-to-noise ratios creating a challenging signal processing problem to monitor the vibrational signature of the device in real-time. To detect/classify a particular type of device from noisy vibration data, it is necessary to identify signatures that make it unique. Resonant (modal) frequencies emitted offer a signature characterizing its operation. The monitoring of structural modes to determine the condition of a device under investigation is essential, especially if it is a critical entity of an operational system. The development of a model-based scheme capable of the on-line tracking of structural modal frequencies by applying both system identification methods to extract a modal model and state estimation methods to track their evolution is discussed along with the development of an on-line monitor capable of detecting anomalies in real-time. An application of this approach to an unknown structural device is discussed illustrating the approach and evaluating its performance. (C) 2017 Acoustical Society of America.
机译:在嘈杂环境中运行的机械设备导致低信噪比,创建一个具有挑战性的信号处理问题,以实时监控设备的振动签名。要从嘈杂的振动数据检测/分类特定类型的设备,必须识别使其独特的签名。谐振(模态)频率发出的签名表征其操作。监测结构模式以确定正在调查的设备的状况至关重要,特别是如果它是操作系统的关键实体。通过应用系统识别方法来提取模型模型和状态估计方法,能够在线模型和状态估计方法进行结构模频频率的基于模型的基于方案的开发,以跟踪它们的演进。随着在线监视器的开发,讨论了跟踪其演化能够实时检测异常。讨论了这种方法对未知结构装置的应用,示出了方法并评估其性能。 (c)2017年声学社会。

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