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Signal Processing Techniques for Vibration-Based Health Monitoring of Smart Structures

机译:基于振动的智能结构健康监测的信号处理技术

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Signal processing is the key component of any vibration-based structural health monitoring (SHM). The goal of signal processing is to extract subtle changes in the vibration signals in order to detect, locate and quantify the damage and its severity in the structure. This paper presents a state-of-the-art review of recent articles on signal processing techniques for vibration-based SHM. The focus is on civil structures including buildings and bridges. The paper also presents new signal processing techniques proposed in the past few years as potential candidates for future SHM research. The biggest challenge in realization of health monitoring of large real-life structures is automated detection of damage out of the huge amount of very noisy data collected from dozens of sensors on a daily, weekly, and monthly basis. The new methodologies for on-line SHM should handle noisy data effectively, and be accurate, scalable, portable, and efficient computationally.
机译:信号处理是任何基于振动的结构健康监测(SHM)的关键组成部分。信号处理的目的是提取振动信号中的细微变化,以便检测,定位和量化结构中的损伤及其严重程度。本文介绍了有关基于振动的SHM的信号处理技术的最新文章的最新进展。重点是土木结构,包括建筑物和桥梁。本文还介绍了在过去几年中提出的新信号处理技术,它们可能成为未来SHM研究的潜在候选者。实现大型现实结构的健康监控所面临的最大挑战是,每天,每周和每月从数十个传感器收集的大量非常嘈杂的数据中自动检测损坏。在线SHM的新方法应有效处理嘈杂的数据,并在计算上做到准确,可扩展,可移植且高效。

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