A Novel Data Reduction Approach for Structural Health Monitoring Systems
A Novel Data Reduction Approach for Structural Health Monitoring Systems
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DOI：
10.3390/s19224823
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发表时间：
2019-11
期刊：
影响因子：
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通讯作者：
H. Bolandi;N. Lajnef;Pengcheng Jiao;Kaveh Barri;Hassene Hasni;A. Alavi
中科院分区：
文献类型：
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作者：
H. Bolandi;N. Lajnef;Pengcheng Jiao;Kaveh Barri;Hassene Hasni;A. Alavi
结构健康监测（SHM）系统产生的大量数据通常会影响系统的数据传输和分析能力。本文提出了一种新的概念，基于概率理论的数据约简SHM系统。所提出的方法的美丽的显着特点是，它减轻了负担的收集和分析的整个应变数据通过相对损伤的方法。在这种方法中，应变分布的变化率与损伤率有关。为了验证该方法的准确性，进行了实验和数值研究的薄钢板承受循环面内拉伸载荷。在钢板上开不同尺寸的圆孔以确定损伤状态。而不是测量整个应变响应，在不同的预定义的应变水平的应变事件的累积持续时间，获得每个损坏的情况。然后，计算的累积次数的分布被用来检测损伤进展。结果表明，该方法能有效地检测结构的损伤进程。通过增加预定义的应变水平，可以提高损伤检测的准确性。所提出的概念可以导致超过2500%的减少数据存储的要求，这可能是特别重要的数据生成和数据处理在线SHM系统。
The massive amount of data generated by structural health monitoring (SHM) systems usually affects the system’s capacity for data transmission and analysis. This paper proposes a novel concept based on the probability theory for data reduction in SHM systems. The beauty salient feature of the proposed method is that it alleviates the burden of collecting and analysis of the entire strain data via a relative damage approach. In this methodology, the rate of variation of strain distributions is related to the rate of damage. In order to verify the accuracy of the approach, experimental and numerical studies were conducted on a thin steel plate subjected to cyclic in-plane tension loading. Circular holes with various sizes were made on the plate to define damage states. Rather than measuring the entire strain response, the cumulative durations of strain events at different predefined strain levels were obtained for each damage scenario. Then, the distribution of the calculated cumulative times was used to detect the damage progression. The results show that the presented technique can efficiently detect the damage progression. The damage detection accuracy can be improved by increasing the predefined strain levels. The proposed concept can lead to over 2500% reduction in data storage requirement, which can be particularly important for data generation and data handling in on-line SHM systems.