...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Mechanical systems and signal processing >Electromechanical properties identification for groups of piezoelectric energy harvester based on Bayesian inference
【24h】

Electromechanical properties identification for groups of piezoelectric energy harvester based on Bayesian inference

机译：基于贝叶斯推理的压电能源收割机组机电特性识别

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

A framework that allows the use of well-known dynamic estimators to infer the electromechanical properties in Piezoelectric Energy Harvesters (PEHs) is presented here. The framework is based on Bayesian inference applied over experimental results obtained from Frequency Response Functions (FRFs). The posterior probability density function is approximated adopting the Transitional Markov Chain Monte Carlo algorithm. A similar approach has been developed recently to perform the electromechanical properties updating for a single PEH. However, our results show that the former approach is not suitable to update the properties associated to a set of PEHs since it mismatches the normalized FRF. The proposed framework extends the previous formulation to solve this issue. The likelihood function is modified to account for a predictive model with three outputs obtained by manipulating the information available in the FRF. The proposed framework in this contribution can be used by manufacturers to update the nominal properties of groups of devices and, simultaneously, to identify the variability induced by the manufacturing process.
机译：这里介绍了一种允许使用众所周知的动态估计来推断压电能量收割机（PEHS）的机电性能的框架。该框架基于应用于从频率响应函数（FRF）获得的实验结果的贝叶斯推断。后验概率密度函数近似采用过渡马尔可夫链蒙特卡罗算法。最近已经开发了类似的方法来执行用于单个PEH的机电性能。但是，我们的结果表明，前一种方法不适合更新与一组PEH相关的属性，因为它不匹配标准化的FRF。所提出的框架扩展了先前的配方来解决这个问题。修改似然函数以解释具有通过操纵FRF中可用的信息而获得的三个输出的预测模型。制造商可以使用本贡献中提出的框架来更新设备组的标称性质，并同时识别制造过程引起的变异性。

著录项

  • 来源
    《Mechanical systems and signal processing》 |2022年第1期|108034.1-108034.14|共14页
  • 作者

    Patricio Peralta; Rafael O. Ruiz; Hussein Rappel; Stephane P.A. Bordas;

  • 作者单位

    Department of Mechanical Engineering Universidad de Chile Santiago Chile Uncertainty Quantification Croup Center for Modem Computational Engineering Universidad de Chile Chile;

    Uncertainty Quantification Croup Center for Modem Computational Engineering Universidad de Chile Chile Department of Civil Engineering Universidad de Chile Santiago Chile;

    The Alan Turing Institute London UK;

    Department of Engineering Institute of Computational Engineering University of Luxembourg Luxembourg Institute of Mechanics and Advanced Materials School of Engineering Cardiff University UK Institute of Research and Development Duy Tan University Danang Vietnam;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Bayesian inference; Piezoelectric energy harvesting; Uncertainty;

    机译：贝叶斯推理;压电能量收获;不确定;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号