Wind and Structures

  • 제36권5호
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  • Pages.345-354
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  • 2023
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  • 1226-6116(pISSN)
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  • 1598-6225(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

A proof-of-concept study of estimating wind speed from acoustic frequency-domain signal using machine learning

  • Yang Ling (National Key Laboratory of Bridge Intelligent and Green Construction, Southwest Jiaotong University) ;
  • Zilong Ti (National Key Laboratory of Bridge Intelligent and Green Construction, Southwest Jiaotong University) ;
  • Hengrui You (National Key Laboratory of Bridge Intelligent and Green Construction, Southwest Jiaotong University) ;
  • Yongle Li (National Key Laboratory of Bridge Intelligent and Green Construction, Southwest Jiaotong University)
  • 투고 : 2022.08.26
  • 심사 : 2023.01.14
  • 발행 : 2023.05.25
⟨ 이전 논문 다음 논문 ⟩

초록

Wind speed measurement is one of the most fundamental tasks for multidiscipline applications and plays an important role in the design and maintenance of modern infrastructures. Wind speed is usually measured using conventional gauges which require additional connections to sensors or collection boxes, and their complex operating principles make these devices largely serve only professionals. This study proposed a novel framework associated with a machine learning architecture to estimate wind speed directly from acoustic signal collected using smartphones. The one-dimensional convolutional network is employed to characterize the underlying relationship between the frequency domain features of the acoustic signal and wind speed. An experimental dataset is collected in wind tunnel laboratory in which the wind speed is measured using cobra probe and the acoustic signal is recorded using smartphone. The influence of encountering direction angle on the 1D-CNN wind speed measurement model is also discussed, as well as the ability of the model to resist noise. The favorable robustness and generalization performance of the 1D-CNN model are verified from multiple perspectives, illustrating the feasibility and practical value of using smartphones to measure wind speed.

키워드

과제정보

The financial support from the National Natural Science Foundation of China (52008349), the Postdoctoral Science Foundation of China (2020M683356, 2021T140573), Natural Science Foundation of Sichuan Province (2022NSFSC1163) and the Fundamental Research Funds for the Central Universities (2682021CX004) are greatly appreciated by the authors.

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