Numerical analysis and optimization of noises of ship cabins in the low frequency

Xu, Yanling; Huang, X; Zhu, Longtu; Huang, Dongyan

doi:10.21595/jve.2017.17933

Cited by 8 publications

(2 citation statements)

References 14 publications

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“…In the case of occupational medicine in the field of hearing testing, it is based on experimental, repeatedly repeated measurements, and the assessment of the results with a varying degree of detail. It should be noted that some researchers are also involved in modeling acoustic phenomena [ 26 ]. In the shipping industry, on the ships, the main noise sources are machinery spaces.…”

Section: Noise Survey Objectives and Sourcesmentioning

confidence: 99%

Occupational Noise on Floating Storage and Offloading Vessels (FSO)

Rutkowski

Korzeb

2021

Sensors

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The purpose and scope of this paper are to provide guidance of the potential impacts of being subjected to high level noise recorded on 1st generation (30 years old) floating storage and offloading vessels (FSO) in sector offshore. The international community recognizes that vibroacoustic impacts from commercial ships may have negative consequences for both humans (worker’s) and marine life, especially marine mammals. As regards the effect of noise on human health, there are legal requirements imposing the noise exposure control on personnel working on ships. The acceptable noise exposure standards are established in European Union Directive 2003/10/EC (2003), the NOPSEMA Regulation (2006), the Maritime Labor Convention (MLC) guidelines (2006), and the recommendations of the International Maritime Organization IMO contained, e.g., IMO MEPC.1/Circ.833 (2014). These regulations inform employers and employees what they must do to effectively protect both the marine environment and the health and life safety of workers employed in the maritime industry offshore. This study also presents an analysis of the results of noise measurements carried out on exemplary 1st generation FSO units.

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Section: Noise Survey Objectives and Sourcesmentioning

confidence: 99%

Occupational Noise on Floating Storage and Offloading Vessels (FSO)

Rutkowski

Korzeb

2021

Sensors

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“…Numerical analysis methods are more popular at present. It includes statistical energy analysis (SEA) [ 2 – 4 ], finite element analysis (FEA) [ 5 , 6 ], the combination of SEA and FEA [ 7 – 10 ], and other methods [ 11 , 12 ]. The numerical methods significantly promotes the development of the research on vibration and noise in ships.…”

Section: Introductionmentioning

confidence: 99%

Machine learning based method for analyzing vibration and noise in large cruise ships

Wu,

He,

Hao

et al. 2024

PLoS ONE

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Cruise ships are distinguished as special passenger ships, transporting passengers to various ports and giving importance to comfort. High comfort can attract lots of passengers and generate substantial profits. Vibration and noise are the most important indicators for assessing the comfort of cruise ships. Existing methods for analyzing vibration and noise data have shown limitations in uncovering essential information and discerning critical disparities in vibration and noise levels across different ship districts. Conversely, the rapid development in machine learning present an opportunity to leverage sophisticated algorithms for a more insightful examination of vibration and noise aboard cruise ships. This study designed a machine learning-driven approach to analyze the vibration and noise data. Drawing data from China’s first large-scale cruise ship, encompassing 127 noise samples, this study sets up a classification task, where decks were assigned as labels and frequencies served as features. Essential information was extracted by investigating this problem. Several machine learning algorithms, including feature ranking, selection, and classification algorithms, were adopted in this method. One or two essential noise frequencies related to each of the decks, except the 10th deck, were obtained, which were partly validated by the traditional statistical methods. Such findings were helpful in reducing and controlling the vibration and noise in cruise ships. Furthermore, the study develops a classifier to distinguish noise samples, which utilizes random forest as the classification algorithm with eight optimal frequency features identified by LightGBM. This classifier yielded a Matthews correlation coefficient of 0.3415. This study gives a new direction for investigating vibration and noise in ships.

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Prediction Modeling Methods

Fischer,

Boroditsky

2024

Noise and Vibration Control on Ships

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Numerical analysis and optimization of noises of ship cabins in the low frequency

Cited by 8 publications

References 14 publications

Occupational Noise on Floating Storage and Offloading Vessels (FSO)

Occupational Noise on Floating Storage and Offloading Vessels (FSO)

Machine learning based method for analyzing vibration and noise in large cruise ships

Prediction Modeling Methods

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