• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

一种基于Frobenius范数和核混合范数惩罚的鲁棒主成分分析及分解与重构的对称点模式提取方法

A Symmetrized Dot Pattern Extraction Method Based on Frobenius and Nuclear Hybrid Norm Penalized Robust Principal Component Analysis and Decomposition and Reconstruction.

作者信息

Wang Lijing, Wei Shichun, Xi Tao, Li Hongjiang

机构信息

School Control and Mechanical Engineering, Tianjin Chengjian University, Tianjin 300384, China.

School of Mechanical Engineering, Tiangong University, Tianjin 300387, China.

出版信息

Sensors (Basel). 2023 Oct 17;23(20):8509. doi: 10.3390/s23208509.

DOI:10.3390/s23208509
PMID:37896602
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10611354/
Abstract

Due to their symmetrized dot pattern, rolling bearings are more susceptible to noise than time-frequency characteristics. Therefore, this article proposes a symmetrized dot pattern extraction method based on the Frobenius and nuclear hybrid norm penalized robust principal component analysis (FNHN-RPCA) as well as decomposition and reconstruction. This method focuses on denoising the vibration signal before calculating the symmetric dot pattern. Firstly, the FNHN-RPCA is used to remove the non-correlation between variables to realize the separation of feature information and interference noise. After, the residual interference noise, irrelevant information, and fault features in the separated signal are clearly located in different frequency bands. Then, the ensemble empirical mode decomposition is applied to decompose this information into different intrinsic mode function components, and the improved DPR/KLdiv criterion is used to select components containing fault features for reconstruction. In addition, the symmetrized dot pattern is used to visualize the reconstructed signal. Finally, method validation and comparative analysis are conducted on the CWRU datasets and experimental bench data, respectively. The results show that the improved criteria can accurately complete the screening task, and the proposed method can effectively reduce the impact of strong noise interference on SDPs.

摘要

由于其对称点模式,滚动轴承对噪声的敏感度高于对时频特征的敏感度。因此,本文提出了一种基于弗罗贝尼乌斯和核混合范数惩罚鲁棒主成分分析(FNHN-RPCA)以及分解与重构的对称点模式提取方法。该方法在计算对称点模式之前着重对振动信号进行去噪。首先,使用FNHN-RPCA去除变量间的不相关性,以实现特征信息与干扰噪声的分离。之后,分离信号中的残余干扰噪声、无关信息和故障特征清晰地位于不同频带。然后,应用总体经验模态分解将该信息分解为不同的固有模态函数分量,并使用改进的DPR/KLdiv准则选择包含故障特征的分量进行重构。此外,利用对称点模式对重构信号进行可视化。最后,分别在CWRU数据集和实验台数据上进行方法验证和对比分析。结果表明,改进后的准则能够准确完成筛选任务,且所提方法能够有效降低强噪声干扰对对称点模式的影响。

相似文献

1
A Symmetrized Dot Pattern Extraction Method Based on Frobenius and Nuclear Hybrid Norm Penalized Robust Principal Component Analysis and Decomposition and Reconstruction.一种基于Frobenius范数和核混合范数惩罚的鲁棒主成分分析及分解与重构的对称点模式提取方法
Sensors (Basel). 2023 Oct 17;23(20):8509. doi: 10.3390/s23208509.
2
Frobenius and nuclear hybrid norm penalized robust principal component analysis for transient impulsive feature detection of rolling bearings.
ISA Trans. 2020 May;100:373-386. doi: 10.1016/j.isatra.2019.11.021. Epub 2019 Nov 25.
3
Fault Feature Extraction Method for Rolling Bearings Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Variational Mode Decomposition.基于自适应噪声的完备总体经验模态分解和变分模态分解的滚动轴承故障特征提取方法
Sensors (Basel). 2023 Nov 27;23(23):9441. doi: 10.3390/s23239441.
4
Intelligent Rolling Bearing Fault Diagnosis Method Using Symmetrized Dot Pattern Images and CBAM-DRN.基于对称点模式图像和 CBAM-DRN 的智能滚动轴承故障诊断方法
Sensors (Basel). 2022 Dec 17;22(24):9954. doi: 10.3390/s22249954.
5
A Novel Fault Detection Method for Rolling Bearings Based on Non-Stationary Vibration Signature Analysis.基于非平稳振动特征分析的滚动轴承新型故障检测方法。
Sensors (Basel). 2019 Sep 16;19(18):3994. doi: 10.3390/s19183994.
6
A New Method Based on Time-Varying Filtering Intrinsic Time-Scale Decomposition and General Refined Composite Multiscale Sample Entropy for Rolling-Bearing Feature Extraction.一种基于时变滤波本征时间尺度分解和广义精细复合多尺度样本熵的滚动轴承特征提取新方法。
Entropy (Basel). 2021 Apr 11;23(4):451. doi: 10.3390/e23040451.
7
An improved complementary ensemble empirical mode decomposition with adaptive noise and its application to rolling element bearing fault diagnosis.一种改进的带自适应噪声的互补总体经验模态分解及其在滚动轴承故障诊断中的应用。
ISA Trans. 2019 Aug;91:218-234. doi: 10.1016/j.isatra.2019.01.038. Epub 2019 Jan 31.
8
Research on Fault Diagnosis of Rolling Bearings Based on Variational Mode Decomposition Improved by the Niche Genetic Algorithm.基于小生境遗传算法改进的变分模态分解的滚动轴承故障诊断研究
Entropy (Basel). 2022 Jun 14;24(6):825. doi: 10.3390/e24060825.
9
A Compound fault diagnosis for rolling bearings method based on blind source separation and ensemble empirical mode decomposition.一种基于盲源分离和总体经验模态分解的滚动轴承复合故障诊断方法。
PLoS One. 2014 Oct 7;9(10):e109166. doi: 10.1371/journal.pone.0109166. eCollection 2014.
10
Optimal Time Frequency Fusion Symmetric Dot Pattern Bearing Fault Feature Enhancement and Diagnosis.最优时频融合对称点模式轴承故障特征增强与诊断
Sensors (Basel). 2024 Jun 27;24(13):4186. doi: 10.3390/s24134186.

本文引用的文献

1
Novel Bearing Fault Diagnosis Using Gaussian Mixture Model-Based Fault Band Selection.基于高斯混合模型的故障频段选择的新型轴承故障诊断
Sensors (Basel). 2021 Oct 1;21(19):6579. doi: 10.3390/s21196579.
2
Frobenius and nuclear hybrid norm penalized robust principal component analysis for transient impulsive feature detection of rolling bearings.
ISA Trans. 2020 May;100:373-386. doi: 10.1016/j.isatra.2019.11.021. Epub 2019 Nov 25.
3
Rub-Impact Fault Diagnosis Using an Effective IMF Selection Technique in Ensemble Empirical Mode Decomposition and Hybrid Feature Models.基于集合经验模态分解和混合特征模型的有效 IMF 选择技术的碰摩故障诊断。
Sensors (Basel). 2018 Jun 26;18(7):2040. doi: 10.3390/s18072040.
4
Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications.用于鲁棒主成分分析的双线性因子矩阵范数最小化:算法与应用
IEEE Trans Pattern Anal Mach Intell. 2018 Sep;40(9):2066-2080. doi: 10.1109/TPAMI.2017.2748590. Epub 2017 Sep 4.
5
Determining embedding dimension for phase-space reconstruction using a geometrical construction.使用几何构造确定相空间重构的嵌入维数。
Phys Rev A. 1992 Mar 15;45(6):3403-3411. doi: 10.1103/physreva.45.3403.
6
On the use of symmetrized dot patterns for the visual characterization of speech waveforms and other sampled data.
J Acoust Soc Am. 1986 Sep;80(3):955-60. doi: 10.1121/1.393918.