Novel direct remaining useful life estimation of aero-engines with randomly assigned hidden nodes | |
Bai, Jian-Ming1,2; Zhao, Guang-She3; Rong, Hai-Jun1 | |
作者部门 | 光学定向与测量技术研究室 |
2020-09 | |
发表期刊 | NEURAL COMPUTING & APPLICATIONS |
ISSN | 0941-0643;1433-3058 |
卷号 | 32期号:18(SI)页码:14347-14358 |
产权排序 | 1 |
摘要 | This paper aims to improve data-driven prognostics by presenting a novel approach of directly estimating the remaining useful life (RUL) of aero-engines without requiring setting any failure threshold information or estimating degradation states. Specifically, based on the sensory data, RUL estimations are directly obtained through the universal function approximation capability of the extreme learning machine (ELM) algorithm. To achieve this, the features related with the RUL are first extracted from the sensory data as the inputs of the ELM model. Besides, to optimize the number of observed sensors, three evaluation metrics of correlation, monotonicity and robustness are defined and combined to automatically select the most relevant sensor values for more effective and efficient remaining useful life predictions. The validity and superiority of the proposed approach is evaluated by the widely used turbofan engine datasets from NASA Ames prognostics data repository. The proposed approach shows improved RUL estimation applicability at any time instant of the degradation process without determining the failure thresholds. This also simplifies the RUL estimation procedure. Moreover, the random properties of hidden nodes in the ELM learning mechanisms ensures the simplification and efficiency for real-time implementation. Therefore, the proposed approach suits to real-world applications in which prognostics estimations are required to be fast. |
关键词 | Remaining useful life (RUL) Aero-engines Extreme learning machine (ELM) |
DOI | 10.1007/s00521-019-04478-1 |
收录类别 | SCI ; EI |
语种 | 英语 |
WOS记录号 | WOS:000575651700010 |
出版者 | SPRINGER LONDON LTD |
EI入藏号 | 20194407592745 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.opt.ac.cn/handle/181661/93739 |
专题 | 光学定向与测量技术研究室 |
通讯作者 | Rong, Hai-Jun |
作者单位 | 1.Xi An Jiao Tong Univ, Sch Aerosp, State Key Lab Strength & Vibrat Mech Struct, Shaanxi Key Lab Environm & Control Flight Vehicle, Xian 710049, Peoples R China 2.Chinese Acad Sci, Opt Direct & Pointing Tech Res Dept, Xian Inst Opt & Precis Mech, Xian 710119, Peoples R China 3.Xi An Jiao Tong Univ, Sch Elect & Informat Engn, Xian 710049, Peoples R China |
推荐引用方式 GB/T 7714 | Bai, Jian-Ming,Zhao, Guang-She,Rong, Hai-Jun. Novel direct remaining useful life estimation of aero-engines with randomly assigned hidden nodes[J]. NEURAL COMPUTING & APPLICATIONS,2020,32(18(SI)):14347-14358. |
APA | Bai, Jian-Ming,Zhao, Guang-She,&Rong, Hai-Jun.(2020).Novel direct remaining useful life estimation of aero-engines with randomly assigned hidden nodes.NEURAL COMPUTING & APPLICATIONS,32(18(SI)),14347-14358. |
MLA | Bai, Jian-Ming,et al."Novel direct remaining useful life estimation of aero-engines with randomly assigned hidden nodes".NEURAL COMPUTING & APPLICATIONS 32.18(SI)(2020):14347-14358. |
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Novel direct remaini(1783KB) | 期刊论文 | 出版稿 | 限制开放 | CC BY-NC-SA | 请求全文 |
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