A novel fault prognostic approach based on particle filters and differential evolution

Cosme Luciana B.; DAngelo Marcos F. S. V.; Caminhas Walmir M.; Yin Shen; Palhares Reinaldo M.

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A novel fault prognostic approach based on particle filters and differential evolution

机译：一种基于粒子过滤器和差分演化的新型故障预后方法

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This paper proposes an improved fault prognostic approach based on a modified particle filter with a built-in differential evolution characteristic. The main methodological contribution of this study is to handle the problem of sample impoverishment faced by particle filters when only a few particles are resampled. This is done by incorporating modified mutation and selection operators for differential evolution into the proposed particle filter. The proposed method is performed to deal with two real applications of condition monitoring and fault prognosis, namely an accelerated degradation of bearings under operating conditions from the platform PRONOSTIA and a high-speed computer numerical control (CNC) milling machine 3-flute cutters.

机译：本文提出了一种基于具有内置差分演化特性的改进粒子滤波器的改进的故障预后方法。该研究的主要方法论贡献是处理仅重采样几种颗粒时颗粒过滤器面临的样品贫困问题。这是通过将修改的突变和选择操作员结合到所提出的粒子过滤器中的修饰突变和选择操作员来完成。该提出的方法是为了处理条件监测和故障预后的两个真正应用，即在从平台的手边和高速计算机数控（CNC）铣削机3-长笛切割器中的运行条件下的轴承的加速劣化。

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来源
《Applied Intelligence: The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies》 |2018年第4期|共20页
作者
Cosme Luciana B.; DAngelo Marcos F. S. V.; Caminhas Walmir M.; Yin Shen; Palhares Reinaldo M.;
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作者单位

Fed Inst Norte Minas Gerais Campus Montes Claros Montes Claros Brazil;

UNIMONTES Dept Comp Sci Ave Rui Braga Sn Vila Mauriceia Montes Claros Brazil;

Univ Fed Minas Gerais Dept Elect Engn Belo Horizonte MG Brazil;

Harbin Inst Technol Harbin Heilongjiang Peoples R China;

Univ Fed Minas Gerais Dept Elect Engn Belo Horizonte MG Brazil;

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原文格式 PDF
正文语种 eng
中图分类自动化技术、计算机技术;
关键词
Differential evolution; Fault prognostic; Particle filters;

机译：差分进化;故障预后;粒子过滤器;

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专利

1. A novel fault prognostic approach based on particle filters and differential evolution [J] . Cosme Luciana B., DAngelo Marcos F. S. V., Caminhas Walmir M., Applied Intelligence: The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies . 2018,第4期

机译：一种基于粒子过滤器和差分演化的新型故障预后方法
2. Prognostics of IGBT modules based on the approach of particle filtering [J] . Lu Yizhou, Christou Aris Microelectronics & Reliability . 2019,第JANa期

机译：基于粒子滤波方法的IGBT模块预测
3. A particle filtering and kernel smoothing-based approach for new design component prognostics [J] . Yang Hu, Piero Baraldi, Francesco Di Maio, Reliability Engineering & System Safety . 2015,第feba期

机译：基于粒子滤波和核平滑的新设计组件预测方法
4. A Particle Filtering Based Approach for Transformer Winding Degradation Prognostics [C] . Haifeng Guo, Aidong Xu, Kai Wang, Prognostics and System Health Management Conference . 2018

机译：基于粒子滤波的变压器绕组退化预测方法
5. A particle filtering-based framework for on-line fault diagnosis and failure prognosis. [D] . Orchard, Marcos E. 2007

机译：基于粒子过滤的在线故障诊断和故障预测框架。
6. A Particle Filtering Approach for Fault Detection and Isolation of UAV IMU Sensors: Design Implementation and Sensitivity Analysis [O] . Egidio D’Amato, Vito Antonio Nardi, Immacolata Notaro, 2021

机译：UAV IMU传感器故障检测和隔离的粒子过滤方法：设计实现和敏感性分析
7. A particle filtering and kernel smoothing-based approach for new design component prognostics [O] . Yang Hu, Piero Baraldi, Francesco Di Maio, 2015

机译：新设计组件预测的粒子滤波和基于内核平滑的方法

A novel fault prognostic approach based on particle filters and differential evolution

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