ABSTRACT This study presents a novel deep learning‐based approach for fault detection in offshore wind‐hydrogen systems. A fault detection model is developed using convolutional neural networks (CNNs), bidirectional long short‐term memory networks (BiLSTMs), and an attention mechanism (AM). The model is trained on a dataset generated through fault injection techniques, which simulate real‐world faults in the system. Key operational parameters, such as wind speed and hydrogen production rate, are used to detect faults effectively. This paper reduces reliance on actual experiments, and introducing artificial faults allows system performance assessment under different fault scenarios, lowering project risks and costs. This work facilitates automatic feature extraction and high‐precision classification of time‐series fault data, which covers a fully automated learning process from data to fault detection. The outstanding performance of the method is validated through computation and result comparison.

Tianxiang Zhao

Li Sun

Yilai Zhou

Zhuang Kang

He Li

Jichuan Kang

Quality and Reliability Engineering International

QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL 是一本致力于质量和可靠性的实际工程方面的期刊。每年出版八次的技术期刊，涵盖现有理论方法、研究和工业实践的发展和实际应用。期刊中的文章将涉及案例研究、教程类型的评论，以及将新的或著名的理论应用于解决工程中实际的质量和可靠性问题。描述使用数学和统计工具解决实际问题的论文鼓励生命工业问题，前提是重点放在实际应用和示范案例研究上。期刊的范围旨在包括电子、电气、机械和系统工程领域的组件、故障物理、设备和系统.该期刊涵盖通信、航空航天、汽车、铁路、船舶设备、控制工程和消费产品等领域。涵盖硬件和软件的质量和可靠性。鼓励发表关于软件工程及其对产品质量和可靠性的影响的论文。该杂志还将涵盖工程行业的质量和可靠性管理。每年出版关于各种关键主题的特刊，并有助于提高质量和可靠性工程国际作为其领域的主要参考。

Quality and Reliability Engineering International is a journal dedicated to the practical engineering aspects of quality and reliability. Published eight times a year, it covers the development and application of existing theoretical methods, research, and industrial practices. Articles in the journal include case studies, tutorial-style reviews, and applications of new or established theories to solve real-world quality and reliability issues in engineering. We encourage papers that use mathematical and statistical tools to address practical problems, particularly those focusing on life industrial issues, with an emphasis on practical applications and demonstrative case studies. The journal's scope includes components, failure physics, equipment, and systems in the fields of electronic, electrical, mechanical, and systems engineering. It covers areas such as communications, aerospace, automotive, railway, marine equipment, control engineering, and consumer products, addressing both hardware and software quality and reliability. We also encourage submissions on software engineering and its impact on product quality and reliability. Furthermore, the journal addresses quality and reliability management in the engineering industry. Special issues on various key topics are published annually, contributing to the enhancement of Quality and Reliability Engineering International as a leading reference in its field.

《Quality and Reliability Engineering International》是一本专注于质量和可靠性实际工程应用的期刊。该期刊每年出版八期，涵盖现有理论方法、研究成果以及工业实践的发展与应用。期刊中的文章包括案例研究、教程型评论，以及将新的或经典理论应用于解决工程中的实际质量和可靠性问题。我们鼓励使用数学和统计工具解决实际问题的论文，特别是关注生命工业问题，强调实际应用和示范案例研究。期刊的范围涵盖电子、电气、机械和系统工程领域的组件、故障物理、设备和系统。涉及的领域包括通信、航空航天、汽车、铁路、船舶设备、控制工程和消费产品，涵盖硬件和软件的质量与可靠性。我们也鼓励发表关于软件工程及其对产品质量和可靠性的影响的论文。此外，期刊还关注工程行业的质量和可靠性管理。每年会出版关于各种关键主题的特刊，致力于提升《Quality and Reliability Engineering International》作为该领域主要参考的地位。

Category	Quartile
工程技术	3
工程技术, 工程综合	3
工程技术, 运筹学与管理科学	3
工程技术, 工程工业	4

Offshore Wind‐Hydrogen Systems Fault Detection Based on CNN‐BiLSTM‐AM Algorithm

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Journal Info

Category	Quartile
OPERATIONS RESEARCH & MANAGEMENT SCIENCE	2