An End-to-End Deep Learning Framework for Fault Detection in Marine Machinery

Sensors, Journal Year: 2024, Volume and Issue: 24(16), P. 5310 - 5310

Published: Aug. 16, 2024

The Industrial Internet of Things has enabled the integration and analysis vast volumes data across various industries, with maritime sector being no exception. Advances in cloud computing deep learning (DL) are continuously reshaping industry, particularly optimizing operations such as Predictive Maintenance (PdM). In this study, we propose a novel DL-based framework focusing on fault detection task PdM marine operations, leveraging time-series from sensors installed shipboard machinery. is designed scalable cost-efficient software solution, encompassing all stages collection pre-processing at edge to deployment lifecycle management DL models. proposed architecture utilizes Graph Attention Networks (GATs) extract spatio-temporal information provides explainable predictions through feature-wise scoring mechanism. Additionally, custom evaluation metric real-world applicability employed, prioritizing both prediction accuracy timeliness identification. To demonstrate effectiveness our framework, conduct experiments three types open-source datasets relevant PdM: electrical data, bearing datasets, water circulation experiments.

Language: Английский

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The Carbon Emission Reduction Roadmap and Policy of Inland River Ships in the Yangtze River Basin

Journal of Cleaner Production, Journal Year: 2025, Volume and Issue: unknown, P. 145056 - 145056

Published: Feb. 1, 2025

Language: Английский

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AIS Data-Driven Assessment of Shore Side Electricity’s Emission Reduction Potential in China

Transport Policy, Journal Year: 2025, Volume and Issue: unknown

Published: March 1, 2025

Language: Английский

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A Novel Ship Fuel Sulfur Content Estimation Method Using Improved Gaussian Plume Model and Genetic Algorithms

Journal of Marine Science and Engineering, Journal Year: 2025, Volume and Issue: 13(4), P. 690 - 690

Published: March 29, 2025

Maritime transportation plays a vital role in global economic development but is also significant contributor to air pollution, especially through emissions of SO2, NOx, and CO2. Identifying non-compliance with fuel sulfur content regulations crucial for mitigating these environmental impacts, yet current methods face challenges, particularly the absence reliable CO2 concentration data. This study proposes novel inverse calculation framework estimate ship without relying on measurements. An improved Gaussian plume line source model was tailored dispersion characteristics emissions, influencing factors evaluated under varying wind field conditions. The emission intensity inversion formulated as an unconstrained multi-dimensional optimization problem, solved using genetic algorithms. By incorporating consumption data derived from basic information, fuels effectively estimated. Experimental evaluations 30 days monitoring revealed that method successfully identified 2743 ships, overall detection rate 82.72%. Among them, 131 ships were flagged suspected high-sulfur fuel, 111 confirmed be non-compliant via sampling laboratory testing, achieving accuracy 84.73%. These results demonstrate proposed approach offers efficient solution real-time enforcement diverse atmospheric conditions, contributing management maritime transport emissions.

Language: Английский

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Spatial and Temporal Shifts and Driving Mechanisms of Embodied Carbon in Water Transport Trade in BRICS Countries

Water, Journal Year: 2025, Volume and Issue: 17(7), P. 1070 - 1070

Published: April 3, 2025

From an ecological protection perspective, clarifying the spatial and temporal transfer characteristics of embodied carbon in water transport trade among BRICS countries its driving mechanisms is great significance for precise formulation emission reduction policies. This study integrates multi-regional input–output model with LMDI decomposition method to quantitatively analyze bi-directional flow from 1995 2018, along spatio-temporal differentiation patterns. The are decomposed across three dimensions: scale, structure, intensity. By adopting a dual perspective time-series correlation, systematically uncovers cross-regional patterns emissions examines interaction pathways various effects throughout their dynamic evolution. finds that (1) shows trend transnational transfer, China being largest net exporter (35.15 Mt 2018), India South Africa as importers (−32.00 −1.89 respectively), Brazil Russia shifting exporters; (2) scale effect drives growth (contribution values: 1.23~119.72 export trade; 4.88~34.36 import trade), while intensity has suppressive role −59.08~−1.48 −20.56~−5.31 structural complex impact on −17.72~0.45 −6.84~13.93 trade). Optimizing structure can help reduce emissions; (3) higher Southeast Asia Northern Hemisphere, changes China’s (total 2018: 57.01 7.98 trade) significantly affect other countries. Based conclusions study, it suggested should strengthen cooperation achieve regional targets by optimizing transport, promoting energy reforms, advancing green technologies equipment, establishing regulatory system.

Language: Английский

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Quantitative impact of decarbonization options on air pollutants from different ship types

Transportation Research Part D Transport and Environment, Journal Year: 2024, Volume and Issue: 133, P. 104316 - 104316

Published: July 10, 2024

Shipping emits Greenhouse Gases (GHG), contributing to climate change and various air pollutants, posing risks on human health. To address GHG, maritime has responded with increasingly stringent legislations, including recent commitments achieve net-zero emissions by 2050. Substantial investments have been made in cutting-edge technologies, alternative fuels operational strategies ensuring regulations compliance. This paper aims quantitatively evaluate the emission performance of diverse decarbonization options, focusing assessing their potential mitigate GHG addressing pollutants. Our analysis utilizes a new set load-dependent Emission Factors employs Automatic Identification System data for 5 ship classes. While measures moderately reduce emissions, fuel shift alternatives on-board carbon capture storage offer more promising pathway towards pollutants reduction. The outcomes intend provide insights into effectiveness reducing external costs, while serving as valuable resource regulatory authorities.

Language: Английский

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A near real-time carbon accounting framework for the decarbonization of maritime transport

Transportation Research Part E Logistics and Transportation Review, Journal Year: 2024, Volume and Issue: 191, P. 103724 - 103724

Published: Aug. 29, 2024

Language: Английский

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