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Weighted K-NN Classification Method of Bearings Fault Diagnosis With Multi-Dimensional Sensitive Features

机译：具有多维敏感特征的轴承故障诊断的加权K-NN分类方法

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Qingfeng Wang; Shuai Wang; Bingkun Wei; Wenwu Chen; Yufei Zhang;
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1. Improved Bearing Fault Diagnosis by Feature Extraction Based on GLCM, Fusion of Selection Methods, and Multiclass-Naïve Bayes Classification [J] . Mireille Pouyap, Laurent Bitjoka, Etienne Mfoumou, Journal of Signal and Information Processing . 2021,第4期

机译：基于GLCM，选择方法的融合，融合，改进了轴承故障诊断，选择方法，以及多标菌-NA＆amp;＃239; ve Bayes分类
2. A new bearing fault diagnosis approach combining sensitive statistical features with improved multiscale permutation entropy method [J] . Minhas Amrinder Singh, Singh Sukhjeet Knowledge-Based Systems . 2021,第Apra22期

机译：一种新的轴承故障诊断方法，敏感统计功能与改进的多尺度置换熵方法
3. Research on rolling bearing fault diagnosis based on multi-dimensional feature extraction and evidence fusion theory [J] . Jingchao Li, Yulong Ying, Yuan Ren, Royal Society Open Science . 2019,第2期

机译：基于多维特征提取和证据融合理论的滚动轴承故障诊断研究
4. A Method for Rolling Bearing Fault Diagnosis Based on Sensitive Feature Selection and Nonlinear Feature Fusion [C] . Peng Liu, Hongru Li, Peng Ye International Conference on Intelligent Computation Technology and Automation . 2015

机译：基于敏感特征选择和非线性特征融合的滚动轴承故障诊断方法
5. Fault detection, diagnosis and prognosis of rolling element bearings: Frequency domain methods and hidden Markov modeling. [D] . Ocak, Hasan. 2004

机译：滚动轴承的故障检测，诊断和预测：频域方法和隐马尔可夫建模。
6. Research on rolling bearing fault diagnosis based on multi-dimensional feature extraction and evidence fusion theory [O] . Jingchao Li, Yulong Ying, Yuan Ren, 2019

机译：基于多维特征提取和证据融合理论的滚动轴承故障诊断研究
7. Bearing Fault Feature Extraction and Fault Diagnosis Method Based on Feature Fusion [O] . Huibin Zhu, Zhangming He, Juhui Wei, 2021

机译：基于特征融合的轴承故障特征提取与故障诊断方法

Weighted K-NN Classification Method of Bearings Fault Diagnosis With Multi-Dimensional Sensitive Features

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