A sea trial method of hull-mounted sonar using machine learning and numerical experiments

Ho-seong Chang; Chang-hyun Youn; Hyung-in Ra; Kyung-won Lee; Dea-hwan Kim; Ki-man Kim

doi:10.7776/ASK.2024.43.3.293

All Issue

2024 Vol.43, Issue 3 Preview Page Next Page

Research Article

A sea trial method of hull-mounted sonar using machine learning and numerical experiments 기계학습 및 수치실험을 활용한 선체고정형소나 해상 시운전 평가 방안

31 May 2024. pp. 293-304

PDF XML

Abstract

In this paper, efficient and reliable methodologies for conducting sea trials to evaluate the performance of hull-mounted sonar systems is discussed. These systems undergo performance verification during ship construction via sea trials. However, the evaluation procedures often lack detailed consideration of variabilities in detection performance due to seabed topography, seasonal factors. To resolve this issue, temperature and salinity structure data were collected from 1967 to 2022 using ARGO floats and ocean observers data. The paper proposes an efficient and reliable sea trial method incorporating Bellhop modeling. Furthermore, a machine learning model applying a Physics-Informed Neural Networks was developed using the acquired data. This model predicts the sound speed profile at specific points within the sea trial area, reflecting seasonal elements of performance evaluation. In this study, we predicted the seasonal variations in sound speed structure during sea trial operations at a specific location within the trial area. We then proposed a strategy to account for the variability in detection performance caused by seasonal factors, using results from Bellhop modeling.

Keywords

Sound speed profile

Hull-mounted sonar

Transmission loss

Physics-Informed Neural Networks (PINNs)

Sea trial

본 논문에서는 선체고정형소나의 해상 시운전을 효율적이면서 신뢰성 있게 수행하기 위한 방안을 제시하였다. 현재 함 건조 과정에서 선체고정형소나의 해상 시운전 절차에는 해저 지형, 계절적 요인 등에 따른 탐지 성능의 변동성이 세밀하게 반영되어 있지 않다. 문제 해결을 위해 1967년부터 2022년까지의 기간 동안 Array for Real time Geostrophic Oceanography(ARGO) 플로트 및 정선 해양관측 정점 데이터를 통해 수온, 염도 구조를 수집하고, 수집된 데이터를 바탕으로 월별 평균 음속 구조를 분석하였다. Bellhop 모델링을 통해 해상 시운전 구역 내 해저 지형 선택, 선체고정형소나와 표적함의 배치, 음파 전송 방향 및 빔 조향각 설정이 포함된 해상 시운전 세부 수행 방안을 제안하였다. 또한, 획득 데이터를 활용하여 물리정보신경망이 적용된 기계학습 모델을 도출하였다. 이를 통해 해상 시운전 구역 내 특정 지점에서 해상 시운전을 수행하는 시점의 계절적 요소를 반영한 음속 구조를 예측하고, Bellhop 모델링 결과를 통해 계절적 요인에 의한 탐지 성능 변동성을 반영한 해상 시운전 방안을 제시하였다.

키워드

음속 구조

선체고정형소나

전달손실

물리정보신경망

해상 시운전

References

S. H. Lim, Y. H. Han, and C. J. Jang, "Minimization of shadow zone for hull mounted sonar" (in Korean), J. KIMST, 13, 211-217 (2010).

M. S. Sim, J. H. Hwang, and H. S. Jeong, "A study for the standardized test of detection performance on active SONAR system" (in Korean), JKAIS, 22, 737-742 (2021).

10.5762/KAIS.2021.22.10.737

Y. C. Kim, Y. S. Choi, and B. M. Park, "Comparison and analysis on the geophysical data using bathymetric surveying product" (in Korean), J. GIS Assoc. Kr. 17, 89-102 (2009).

C. Amante and B. W. Eakins, "Etopo1 arc-minute global relief model: procedures, data, sources and analysis," NGDC, Tech. Rep., 2003.

National Institute of Meteorological Science, http://argo.nims.go.kr/argo3/, (Last viewed July 2, 2023).

Korea Oceangraphic Data Center, https://www.nifs.go.kr/kodc/soo_st_list.kodc, (Last viewed July 2, 2023).

H. Medwin, "Speed of sound in water: a simple equation for realistic parameters," J. Acoust. Soc. Am. 58, 1349-1359 (1987).

M. Raissi, P. Perdikaris, and G. E. Karniadakis, "Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations," J. Comput. Phys. 378, 686-707 (2019).

10.1016/j.jcp.2018.10.045

L. Alzubaidi, "A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications," J. Big Data, 10, 46 (2023).

10.1186/s40537-023-00727-2

N. Y. Park, Y. G. Kim, K. O. Kim, S. U. Son, J. J. Park, and Y. H. Kim, "Estimation of seasonal representation of the sea water temperature profile using machine learning and its effect on the prediction of underwater acoustic detection performance," Ocean Sci. 57, 528-540 (2022).

10.1007/s12601-022-00086-8

S. C. Lee, S. H. Kim, J. W. Choi, D. H. Kim, J. S. Park, and K. J. Park, "Possibility of false target signal induced by reverberation due to internal waves in shallow water," J. Acoust. Soc. Kr. 34, 98-107 (2015).

10.7776/ASK.2015.34.2.098

S. U. Son, W. K. Kim, H. S. Bae, and J. S. Park, "Assessment of acoustic detection performance for a deployment of bi-static sonar," J. Acoust. Soc. Kr. 41, 419-425 (2022).

A. D. Waite, Sonar for Practicing Engineers, 3rd ed (John Wiley & Sons, Chichester, 2002), pp. 1-336.

H. S. Kim, Sound attenuation by fish schools at mid-frequency through experiments and modeling of detection performance, (Ph.D. Thesis, Jeju National University, 2020).

H. R. Kim and J. W. Choi, "A study on the detection performance of the integrated sonar system operated by surface vessel in the mesoscale eddy in the Southwestern East Sea," J. KNST, 3, 20-45 (2020).

10.31818/JKNST.2020.03.3.1.20

R. J. Urick, Principal of Underwater Sound, Optimum Array Processing, 3rd ed (McGraw-hill Book Company, New York, 1983), pp. 1-442.

K. J. Park and P. C. Chu, "Temporal and spatial variability of sound propagation characteristics in the Northern East China Sea" (in Korean), J. KIMST, 18, 201-211 (2015).

10.9766/KIMST.2015.18.2.201

S. H. Lim and G. H. Ryu, "Underwater acoustic environment and low frequency acoustic transmission in the sub-polar front region of the East Sea" (in Korean), J. KIMST, 12, 415-423 (2009).

F. B. Jensen, W. A. Kuperman, M. B. Porter, and H. Schimidt, Computational Ocean Acoustics, 2nd ed (Springer, New York, 2011), pp. 1-794.

10.1007/978-1-4419-8678-8_1

Y. H. Kim and H. S. Kim, "Seasonal and interannual variability of the north korean cold current in the east sea reanalysis data" (in Korean), Ocean and Polar Research, 30, 21-31 (2008).

10.4217/OPR.2008.30.1.021

W. K. Kim, C. B. Cho, J. S. Park, J. Y. Hahan, and Y. N. Na, "Effects of warm eddy on long-range sound propagation in the East Sea" (in Korean), J. Acoust. Soc. Kr. 34, 455-462 (2015).

10.7776/ASK.2015.34.6.455

Information

Publisher :The Acoustical Society of Korea
Publisher(Ko) :한국음향학회
Journal Title :The Journal of the Acoustical Society of Korea
Journal Title(Ko) :한국음향학회지
Volume : 43
No :3
Pages :293-304
Received Date : 2024-01-19
Revised Date : 2024-03-04
Accepted Date : 2024-03-27
DOI :https://doi.org/10.7776/ASK.2024.43.3.293

The Journal of the Acoustical Society of Korea 한국음향학회지 ISSN:1225-4428(Print) 2287-3775(Online)

All Issue