Deterministic and low-latency time-series forecasting of nonstationary signals
Deterministic and low-latency time-series forecasting of nonstationary signals
复制标题
非平稳信号的确定性和低延迟时间序列预测
DOI：
10.1117/12.2629025
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Hu, Chao
中科院分区：
文献类型：
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作者：
Chowdhury, Puja;Barzegar, Vahid;Satme, Joud;Downey, Austin;Laflamme, Simon;Bakos, Jason D.;Hu, Chao
时间信号的硬实时时间序列预测在结构健康监测与控制领域有着广泛的应用。特别是对于经历高速动力学的结构，这种结构的例子包括高超声速飞行器和空间基础设施。这项工作报告了一种用于结构振动确定性和低延迟在线时间序列预测的软硬件耦合算法的发展，该算法能够对非平稳事件进行学习并在事件发生后调整其预测信号。提出的算法使用了一组离线训练的多层感知器，这些感知器基于与结构相关的实验和模拟数据。然后，使用动态关注层来选择性地缩放各个模型的输出，以在所考虑的预测范围内获得统一的预测信号。通过量化信号的测量值与其先前预测值之间的误差，不断更新动态注意力层的标量值。通过在现场可编程门阵列上的部署，实现了该算法的确定性时序。利用测试结构上的实验数据验证了该算法的性能。结果表明，对于所设计的系统，在KINTEX-7 70T的现场可编程门阵列上实现了25.76µS的系统延迟，并且具有足够的精度。
Hard real-time time-series forecasting of temporal signals has applications in the field of structural health monitoring and control. Particularly for structures experiencing high-rate dynamics, examples of such structures include hypersonic vehicles and space infrastructure. This work reports on the development of a coupled softwarehardware algorithm for deterministic and low-latency online time-series forecasting of structural vibrations that is capable of learning over nonstationary events and adjusting its forecasted signal following an event. The proposed algorithm uses an ensemble of multi-layer perceptrons trained offline on experimental and simulated data relevant to the structure. A dynamic attention layer is then used to selectively scale the outputs of the individual models to obtain a unified forecasted signal over the considered prediction horizon. The scalar values of the dynamic attention layer are continuously updated by quantifying the error between the signal’s measured value and its previously predicted value. Deterministic timing of the proposed algorithm is achieved through its deployment on a field programmable gate array. The performance of the proposed algorithm is validated on experimental data taken on a test structure. Results demonstrate that a total system latency of 25.76 µs can be achieved on a Kintex-7 70T FPGA with sufficient accuracy for the considered system.
DOI：
--
发表时间：
2021
期刊：
Data Science in Engineering, Volume 9
影响因子：
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作者：
J. Dodson;Austin Downey;S. Laflamme;M. Todd;A. Moura;Yang Wang;Zhu Mao;P. Avitabile;Erik Blasch
通讯作者：
Erik Blasch