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  • Online-Ressource  (4)
  • SAGE Publications  (4)
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  • Online-Ressource  (4)
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  • SAGE Publications  (4)
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  • 1
    Online-Ressource
    Online-Ressource
    Residual life estimation of lithium-ion batteries based on nonlinear Wiener process with measurement error
    SAGE Publications ; 2023
    In:  Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability Vol. 237, No. 1 ( 2023-02), p. 133-151
    Details
    In: Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, SAGE Publications, Vol. 237, No. 1 ( 2023-02), p. 133-151
    Kurzfassung: Residual life (RL) estimation is a key issue in the prognostics and health management (PHM). This paper proposes a heuristic algorithm for RL estimation based on the nonlinear Wiener process with measurement error (ME) and also proposes an unbiased parameters estimation method. First, we use the nonlinear Wiener process with ME to model the degradation process. Then, an analytical expression of parameters estimation results with restriction of the nonlinear coefficient and variance of ME is obtained and an unbiased parameters estimation method is also derived by analyzing the natures of parameters estimation. Moreover, an empirical unbiased parameters estimation method for the degradation data with different measurement times is also proposed. After that, we extend the heuristic algorithm to the nonlinear Wiener process with ME and some relevant conclusions are proved. Finally, some simulation examples and a case study of lithium-ion batteries are used for experimental verification. The results show that the unbiased parameters estimation method is superior to the traditional maximum likelihood estimation (MLE) method and the heuristic RL estimation method can overcome the influence of imperfect prior information for lithium-ion batteries based on the nonlinear Wiener process with ME.
    Materialart: Online-Ressource
    ISSN: 1748-006X , 1748-0078
    URL: Article
    DOI: 10.1177/1748006X221080345
    Sprache: Englisch
    Verlag: SAGE Publications
    Publikationsdatum: 2023
    ZDB Id: 2246471-2
    Standort Signatur Einschränkungen Verfügbarkeit
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    Online-Ressource
  • 2
    Online-Ressource
    Online-Ressource
    Concurrent Fault Diagnosis for Rotating Machinery Based on Vibration Sensors
    SAGE Publications ; 2013
    In:  International Journal of Distributed Sensor Networks Vol. 9, No. 4 ( 2013-04-01), p. 472675-
    Details
    In: International Journal of Distributed Sensor Networks, SAGE Publications, Vol. 9, No. 4 ( 2013-04-01), p. 472675-
    Kurzfassung: Rotating machinery is widely used in modern industry. It is one of the most critical components in a variety of machinery and equipment. Along with the continuous development of science and technology, the structures of rotating machinery become of larger scale, of higher speed, and more complicated, which results in higher probability of concurrent failure in practice. It is important to enable reliable, safe, and efficient operation of large-scale and critical rotating machinery, which requires us to achieve accurate diagnosis of concurrent fault, for example, rolling bearing diagnosis, gearbox diagnosis, and compressor diagnosis. In this paper, to achieve concurrent fault diagnosis for rotating machinery, which cannot be accurately diagnosed by existing methods, we develop an integrated method using artificial immune algorithm and evidential theory.
    Materialart: Online-Ressource
    ISSN: 1550-1477 , 1550-1477
    URL: Article
    DOI: 10.1155/2013/472675
    Sprache: Englisch
    Verlag: SAGE Publications
    Publikationsdatum: 2013
    ZDB Id: 2192922-1
    Standort Signatur Einschränkungen Verfügbarkeit
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    Online-Ressource
  • 3
    Online-Ressource
    Online-Ressource
    Remaining useful life prediction of implicit linear Wiener degradation process based on multi-source information
    SAGE Publications ; 2022
    In:  Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability
    Details
    In: Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, SAGE Publications
    Kurzfassung: Accurate remaining useful life (RUL) prediction is helpful to improve the reliability and safety of complex systems. However, in practical engineering applications, it often occurs imperfect or scarce prior degradation information for the degradation system with measurement error (ME). In order to solve this problem, based on the implicit linear Wiener degradation process, a RUL prediction method which reasonably fuses failure time data or multi-source information is proposed in this paper. Firstly, based on the implicit linear Wiener degradation process, we obtain the relationship between the natures of parameters estimation and degradation data by theoretical derivation, which provides a theoretical basis regarding how to fuse multi-source information. Secondly, according to the natures of parameters estimation, we use field degradation data and historical degradation data to estimate the fixed parameters of the two prediction cases respectively, and fuse failure time data into the degradation model by the expectation maximization (EM) algorithm. Then, the Kalman filtering algorithm is used to online update the drift parameter based on field degradation data. Finally, we use some simulation experiments to further verify the natures of parameters estimation, and two practical case studies to verify the superiority of the proposed method.
    Materialart: Online-Ressource
    ISSN: 1748-006X , 1748-0078
    URL: Article
    DOI: 10.1177/1748006X221132606
    Sprache: Englisch
    Verlag: SAGE Publications
    Publikationsdatum: 2022
    ZDB Id: 2246471-2
    Standort Signatur Einschränkungen Verfügbarkeit
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    Online-Ressource
  • 4
    Online-Ressource
    Online-Ressource
    Degradation modeling–based remaining useful life estimation: A review on approaches for systems with heterogeneity
    SAGE Publications ; 2015
    In:  Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability Vol. 229, No. 4 ( 2015-08), p. 343-355
    Details
    In: Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, SAGE Publications, Vol. 229, No. 4 ( 2015-08), p. 343-355
    Kurzfassung: Prognostics and health management has drawn increasing attention and gained deepening recognition and widening applications during the past decades. Due to offering guidance for sequential managements involving inspection schedule, maintenance, replacement, and spare parts ordering, remaining useful life estimation has been termed as the kernel technology of prognostics and health management and is the focus of this research in the field of reliability. Heterogeneity is widespread in the inner states of a system and its related working environments. This article provides a review on approaches for degradation modeling and remaining useful life estimation, with an emphasis on the heterogeneity in the systems. Approaches for three kinds of heterogeneity, including the unit-to-unit variability, the variability in time-varying operating conditions, and the diversity of tasks and workloads of a system during its lifetime, are summarized consecutively, and the corresponding methods are provided. Merits and drawbacks are summed up, respectively, following each approach. In addition, several possible future research directions are provided at the end of this article.
    Materialart: Online-Ressource
    ISSN: 1748-006X , 1748-0078
    URL: Article
    DOI: 10.1177/1748006X15579322
    Sprache: Englisch
    Verlag: SAGE Publications
    Publikationsdatum: 2015
    ZDB Id: 2246471-2
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
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