Poster + Paper
20 April 2022 Deterministic and low-latency time-series forecasting of nonstationary signals
Author Affiliations +
Conference Poster
Abstract
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.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Puja Chowdhury, Vahid Barzegar, Joud Satme, Austin R. J. Downey, Simon Laflamme, Jason D. Bakos, and Chao Hu "Deterministic and low-latency time-series forecasting of nonstationary signals", Proc. SPIE 12043, Active and Passive Smart Structures and Integrated Systems XVI, 120431D (20 April 2022); https://doi.org/10.1117/12.2629025
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KEYWORDS
Field programmable gate arrays

Clocks

Neurons

Signal to noise ratio

Algorithm development

Damage detection

Data acquisition

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