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Blind Application of Developed Smart Vibration-Based Machine Learning (SVML) Model for Machine Faults Diagnosis to Different Machine Conditions

机译：基于智能振动的机器学习（SVML）模型对不同机器条件的机器故障诊断

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Natalia F. Espinoza Sepúlveda; Jyoti K. Sinha;
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年度 2020
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1. Parameter Optimisation in the Vibration-Based Machine Learning Model for Accurate and Reliable Faults Diagnosis in Rotating Machines [J] . Natalia Espinoza Sepulveda, Jyoti Sinha Machines . 2020,第4期

机译：基于振动的机器学习模型中的参数优化，用于旋转机器准确可靠的故障诊断
2. Comparison of machine learning models based on time domain and frequency domain features for faults diagnosis in rotating machines [J] . Natalia Espinoza Sepulveda, Jyoti Sinha MATEC Web of Conferences . 2018,第1期

机译：基于时域和频域特征的旋转机器故障诊断机器学习模型比较
3. Applications of machine learning to machine fault diagnosis: A review and roadmap [J] . Yaguo Lei, Bin Yang, Xinwei Jiang, Mechanical systems and signal processing . 2020,第Apra期

机译：机器学习在机器故障诊断中的应用：回顾与路线图
4. Comparison of machine learning models based on time domain and frequency domain features for faults diagnosis in rotating machines [C] . Natalia Espinoza Sepulveda, Jyoti Sinha International Conference on Vibration Engineering and Technology of Machinery . 2018

机译：基于时域和频域特征的机器学习模型对旋转机器故障诊断的比较
5. Machine Learning based Early Fault Diagnosis of Induction Motor for Electric Vehicle Application [D] . Ghosh, Eshaan 2018

机译：基于机器学习的电动汽车感应电动机早期故障诊断
6. Applications of Machine Learning Predictive Models in the Chronic Disease Diagnosis [O] . Gopi Battineni, Getu Gamo Sagaro, Nalini Chinatalapudi, 2020

机译：机器学习预测模型在慢性病诊断中的应用
7. Comparison of machine learning models based on time domain and frequency domain features for faults diagnosis in rotating machines [O] . Natalia Espinoza Sepulveda, Jyoti Sinha 2018

机译：基于时域和频域特征的机器学习模型对旋转机器故障诊断的比较

Blind Application of Developed Smart Vibration-Based Machine Learning (SVML) Model for Machine Faults Diagnosis to Different Machine Conditions

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