基于流数据的结构健康实时监测系统

IF 2.1 3区 工程技术 Q2 ENGINEERING, CIVIL
Qilin Zhang, Siyuan Sun, B. Yang, R. Wüchner, Licheng Pan, Haitao Zhu
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引用次数: 2

摘要

提出了一种基于流数据的结构实时健康监测系统。与传统的SHM系统相比,该系统对数据传输和处理进行了一系列优化,以减少延迟,更好地满足实时性要求。采用了流系统中水印的概念,解决了在实时性要求下何时触发时间窗计算的问题。此外,采用了设计良好的并行机制来满足并行数据流的多级计算需求。最后给出了该系统在上海中心大厦的应用实例。以峰值拾取方法为例,在测试环境中跟踪不同并行方案下各主操作的延迟。结果表明,并行计算有效地降低了延迟,为将来将随机减量技术(RDT)、随机子空间识别(SSI)或其他更复杂但有效的并行算法集成到系统中提供了参考。在测试环境下,从数据生成到数据传输到web服务器的总延迟约为200-400 ms,表明系统具有良好的实时性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-time structural health monitoring system based on streaming data
In this paper, a novel real-time structural health monitoring (SHM) system based on streaming data is proposed. In contrast to a traditional SHM system, the proposed system implements a series of optimizations for data transmission and processing to reduce the latency and better satisfy the real-time requirement. The concept of the watermark in the streaming system is adopted to address the problem of when to trigger the time window calculation under the real-time requirement. Moreover, a well-designed parallel mechanism is used to satisfy the multistage computation requirement in the parallel data stream. A case study in which the proposed system is applied to the Shanghai Tower is presented. The peak picking method is used as an example in the test environment to track the latency of each main operation under different parallelism schemes. The results show that computing in parallel effectively reduces the latency and provides a reference for integrating the random decrement technique (RDT), stochastic subspace identification (SSI), or other more complex but effective algorithms in parallel into the system in the future. The total latency under the test environment from data generation to data transmission to the web server is approximately only 200-400 ms, which indicates the excellent real-time performance of the system.
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来源期刊
Smart Structures and Systems
Smart Structures and Systems 工程技术-工程:机械
CiteScore
6.50
自引率
8.60%
发文量
0
审稿时长
9 months
期刊介绍: An International Journal of Mechatronics, Sensors, Monitoring, Control, Diagnosis, and Management airns at providing a major publication channel for researchers in the general area of smart structures and systems. Typical subjects considered by the journal include: Sensors/Actuators(Materials/devices/ informatics/networking) Structural Health Monitoring and Control Diagnosis/Prognosis Life Cycle Engineering(planning/design/ maintenance/renewal) and related areas.
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