Corrigendum to 'A simple and fast guideline for generating enhanced/squared envelope spectra from spectral coherence for bearing fault diagnosis' [Mech. Syst. Sig. Process. 122 (2019) 754-768]

Wang Dong; Zhao Xuejun; Kou Lin-Lin; Qin Yong; Zhao Yang; Tsui Kwok-Leung

首页> 外文期刊>Mechanical systems and signal processing >Corrigendum to 'A simple and fast guideline for generating enhanced/squared envelope spectra from spectral coherence for bearing fault diagnosis' [Mech. Syst. Sig. Process. 122 (2019) 754-768]

【24h】

Corrigendum to 'A simple and fast guideline for generating enhanced/squared envelope spectra from spectral coherence for bearing fault diagnosis' [Mech. Syst. Sig. Process. 122 (2019) 754-768]

机译：更正为“从光谱相干性生成增强/平方包络光谱以进行轴承故障诊断的简单快速指南” [Mech。 Syst。签名处理。 122（2019）754-768]

获取原文

获取原文并翻译 | 示例

掌桥外文数据库（机构版） >>

开具论文收录证明 >>

文献代查 >>

页面导航

著录项
相似文献
相关主题

著录项

来源
《Mechanical systems and signal processing》 |2019年第1期|724-724|共1页
作者
Wang Dong; Zhao Xuejun; Kou Lin-Lin; Qin Yong; Zhao Yang; Tsui Kwok-Leung;
展开▼
作者单位

Shanghai Jiao Tong Univ, State Key Lab Mech Syst & Vibrat, Shanghai 200240, Peoples R China|City Univ Hong Kong, Sch Data Sci, Kowloon, Tat Chee Ave, Hong Kong, Peoples R China;

Beijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing, Peoples R China;

Beijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing, Peoples R China;

Beijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing, Peoples R China;

City Univ Hong Kong, Sch Data Sci, Kowloon, Tat Chee Ave, Hong Kong, Peoples R China;

City Univ Hong Kong, Sch Data Sci, Kowloon, Tat Chee Ave, Hong Kong, Peoples R China;

展开▼
收录信息
原文格式 PDF
正文语种 eng
中图分类
关键词

相似文献

外文文献

1. A simple and fast guideline for generating enhanced/squared envelope spectra from spectral coherence for bearing fault diagnosis [J] . Wang Dong, Zhao Xuejun, Kou Lin-Lin, Mechanical systems and signal processing . 2019,第MAY1期

机译：一种简单快速的指南，用于从频谱相干性生成增强/平方包络频谱以进行轴承故障诊断
2. Fractional envelope to enhance spectral features of rolling element bearing faults [J] . Jahagirdar Ankush C., Gupta Karunesh Kumar Journal of Mechanical Science and Technology . 2020,第2期

机译：分数包络提高滚动元件轴承故障的光谱特征
3. A deep learning method for bearing fault diagnosis based on Cyclic Spectral Coherence and Convolutional Neural Networks [J] . Zhuyun Chen, Alexandre Mauricio, Weihua Li, Mechanical systems and signal processing . 2020,第Juna期

机译：基于循环谱相干和卷积神经网络的轴承故障诊断深度学习方法
4. A Quantitative Fault Diagnosis Method for Rolling Element Bearings Based on Dynamic Model and Fast Spectral Kurtosis [C] . Lingli Cui, Jinfeng Huang, Zong Meng, Prognostics and System Health Management Conference . 2018

机译：基于动力学模型和快速谱峰度的滚动轴承定量故障诊断方法
5. A study of two bispectral features from envelope signals for bearing fault diagnosis [O] . Rehab Ibrahim, Tiana Xiange, Hu Niaoqing, 100

机译：用于轴承故障诊断的包络信号的两个双谱特征研究

Corrigendum to 'A simple and fast guideline for generating enhanced/squared envelope spectra from spectral coherence for bearing fault diagnosis' [Mech. Syst. Sig. Process. 122 (2019) 754-768]

著录项

相似文献

相关主题

期刊订阅