{"title":"Complex Decay Prediction of Marine Machinery Using Multilabel SVM","authors":"Yanghui Tan, Hui Tian, Feixiang Xu, Dingyu Jiang, Ruizheng Jiang, Yejin Lin, Jun-dong Zhang","doi":"10.5957/josr.10200052","DOIUrl":null,"url":null,"abstract":"In this article, a multilabel support vector machine (SVM)-based approach is investigated to address the simultaneous decay detection of the marine propulsion system. To verify the performance of the algorithm, we perform some experiments using a simulation dataset from a real-data validated numerical simulator of a Frigate. In particular, we try to train the model without simultaneous decay data, considering the great difficulty of obtaining simultaneous decay data in practice. The experimental results show that the proposed approach can identify the complex decay modes of the marine propulsion system effectively using only simple decay data in the training process.\n Introduction\n The propulsion system is considered to be the “heart” of a marine ship (Li et al. 2019a). Its safety and reliability are critical to the regular operation of the ship (Bayer et al. 2018; Cheliotis & Lazakis, 2018; Lazakis et al. 2016). However, performance decay may occur to the propulsion system due to the high humidity and high salt characteristics of the marine environment (Fang et al. 2018; Kang et al. 2019; Wang et al. 2019). The decay modes can be divided into single decay and simultaneous decay. Single decay indicates a simple decay mode that only one kind of decay occurs at a time, and simultaneous decay indicates a complex decay mode that multiple decays occur at the same time. To improve the safety and reliability of the marine propulsion system, researchers have proposed many related approaches from the perspective of fault diagnosis.","PeriodicalId":50052,"journal":{"name":"Journal of Ship Research","volume":" ","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Ship Research","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.5957/josr.10200052","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
引用次数: 1
Abstract
In this article, a multilabel support vector machine (SVM)-based approach is investigated to address the simultaneous decay detection of the marine propulsion system. To verify the performance of the algorithm, we perform some experiments using a simulation dataset from a real-data validated numerical simulator of a Frigate. In particular, we try to train the model without simultaneous decay data, considering the great difficulty of obtaining simultaneous decay data in practice. The experimental results show that the proposed approach can identify the complex decay modes of the marine propulsion system effectively using only simple decay data in the training process.
Introduction
The propulsion system is considered to be the “heart” of a marine ship (Li et al. 2019a). Its safety and reliability are critical to the regular operation of the ship (Bayer et al. 2018; Cheliotis & Lazakis, 2018; Lazakis et al. 2016). However, performance decay may occur to the propulsion system due to the high humidity and high salt characteristics of the marine environment (Fang et al. 2018; Kang et al. 2019; Wang et al. 2019). The decay modes can be divided into single decay and simultaneous decay. Single decay indicates a simple decay mode that only one kind of decay occurs at a time, and simultaneous decay indicates a complex decay mode that multiple decays occur at the same time. To improve the safety and reliability of the marine propulsion system, researchers have proposed many related approaches from the perspective of fault diagnosis.
本文研究了一种基于多标签支持向量机(SVM)的船舶推进系统同步衰减检测方法。为了验证该算法的性能,我们使用护卫舰实际数据验证数值模拟器的仿真数据集进行了一些实验。考虑到实际中获取同步衰减数据的难度很大,我们尝试在没有同步衰减数据的情况下训练模型。实验结果表明,该方法在训练过程中仅使用简单的衰减数据就能有效识别舰船推进系统的复杂衰减模式。推进系统被认为是船舶的“心脏”(Li et al. 2019a)。其安全性和可靠性对船舶的正常运行至关重要(Bayer et al. 2018;Cheliotis & Lazakis, 2018;Lazakis et al. 2016)。然而,由于海洋环境的高湿和高盐特性,推进系统可能会出现性能衰减(Fang et al. 2018;Kang et al. 2019;Wang et al. 2019)。衰减模式可分为单次衰减和同步衰减。单一衰变是指一次只发生一种衰变的简单衰变模式,同时衰变是指同时发生多种衰变的复杂衰变模式。为了提高船舶推进系统的安全性和可靠性,研究人员从故障诊断的角度提出了许多相关的方法。
期刊介绍:
Original and Timely technical papers addressing problems of shipyard techniques and production of merchant and naval ships appear in this quarterly publication. Since its inception, the Journal of Ship Production and Design (formerly the Journal of Ship Production) has been a forum for peer-reviewed, professionally edited papers from academic and industry sources. As such, it has influenced the worldwide development of ship production engineering as a fully qualified professional discipline. The expanded scope seeks papers in additional areas, specifically ship design, including design for production, plus other marine technology topics, such as ship operations, shipping economic, and safety. Each issue contains a well-rounded selection of technical papers relevant to marine professionals.