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Real-time operational load monitoring of a composite aerostructure using FPGA-based computing system

Mucha Waldemar

Bulletin of the Polish Academy of Sciences. Technical Sciences

2024

Vol. 72, nr 1

art. no. e148251

Operational load monitoring (OLM) is an industrial process related to structural health monitoring, where fatigue of the structure is tracked. Artificial intelligence methods, such as artificial neural networks (ANNs) or Gaussian processes, are utilized to improve efficiency of such processes. This paper focuses on moving such processes towards green computing by deploying and executing the algorithm on low-power consumption FPGA where high-throughput and truly parallel computations can be performed. In the following paper, the OLM process of typical aerostructure (hat-stiffened composite panel) is performed using ANN. The ANN was trained using numerically generated data, of every possible load case, to be working with sensor measurements as inputs. The trained ANN was deployed to Xilinx Artix-7 A100T FPGA of a real-time microcontroller. By executing the ANN on FPGA (where every neuron of a given layer can be processed at the same time, without limiting the number of parallel threads), computation time could be reduced by 70% as compared to standard CPU execution. Series of real-time experiments were performed that have proven the efficiency and high accuracy of the developed FPGA-based algorithm. Adjusting the ANN algorithm to FPGA requirements takes some effort, however it can lead to high performance increase. FPGA has the advantages of many more potential parallel threads than a standard CPU and much lower consumption than a GPU. This is particularly important taking into account potential embedded and remote applications, such as widely performed monitoring of airplane structures.

Green Information Technology Practices among IT Professionals: Theory of Planned Behavior Perspective

Akman I, Mishra A.

Problemy Ekorozwoju

2014

Vol. 9, nr 2

47--54

According to the existing literature, the determinants of environmental attitudes and behavior are important. In this paper impact of information technology adoption environment has been investigated. Some of the studies have successfully utilized Theory of Planned Behavior (TPB) for adoption behavior. This study proposed TPB to explain IT professionals’ intentions for Green Information Technology (GIT) practices. For this purpose, a survey was conducted among IT professionals from public and private sector organizations. Core factors of TPB were included in the analysis. Overall, results revealed that the TPB model explains behavioral intent, and all four core constructs were significant predictors of the intent. Limitations of the study, and implications for theory are also discussed.

Według wskazań literaturowych, determinanty ekologicznych postaw i zachowań odgrywają istotną rolę w ich kształtowaniu i warto badać wpływ, jaki wywierać może na nie stosowanie technologii informatycznych. W tej pracy wykorzystano teorię planowanego zachowania (Theory of Planned Behavior – TPB), aby wyjaśnić podejście profesjonalistów z zakresu IT do praktyk związanych ze stosowaniem zielonych technologii informatycznych (Green Information Technologies – GIT). Badania wśród pracowników IT przeprowadzono w firmach reprezentujących dwa sektory: państwowym i prywatnym. Otrzymane wyniki pokazały, że model TPB, uwzględniający cztery filary, wyjaśnia determinanty odnoszące się do zachowania. W artykule omówiono także napotkane ograniczenia, a także implikacje dla teorii TPB, które z przeprowadzonych badań wynikają.