Li, Naipeng: шукати на сайті Z-Library

Рік:

2018

Мова:

english

Файл:

PDF, 3.20 MB

english, 2018

A recurrent neural network based health indicator for remaining useful life prediction of bearings

Guo, Liang, Li, Naipeng, Jia, Feng, Lei, Yaguo, Lin, Jing

Журнал:

IEEE Transactions on Reliability

Рік:

2017

Мова:

english

Файл:

PDF, 842 KB

english, 2017

A Hybrid Prognostics Approach for Estimating Remaining Useful Life of Rolling Element Bearings

Wang, Biao, Lei, Yaguo, Li, Naipeng, Li, Ningbo

Журнал:

Рік:

2018

Мова:

english

Файл:

PDF, 4.50 MB

english, 2018

Deep Convolutional Transfer Learning Network: A New Method for Intelligent Fault Diagnosis of Machines with Unlabeled Data

Guo, Liang, Lei, Yaguo, Xing, Saibo, Yan, Tao, Li, Naipeng

Журнал:

Рік:

2018

Мова:

english

Файл:

PDF, 1.36 MB

english, 2018

[IEEE 2018 IEEE International Conference on Prognostics and Health Management (ICPHM) - Seattle, WA, USA (2018.6.11-2018.6.13)] 2018 IEEE International Conference on Prognostics and Health Management (ICPHM) - Remaining Useful Life Prediction of Machinery Subjected to Two-Phase Degradation Process

Yan, Tao, Lei, Yaguo, Li, Naipeng

Рік:

2018

Мова:

english

Файл:

PDF, 599 KB

english, 2018

Remaining useful life prediction of machinery under time-varying operating conditions based on a two-factor state-space model

Li, Naipeng, Gebraeel, Nagi, Lei, Yaguo, Bian, Linkan, Si, Xiaosheng

Журнал:

Рік:

2019

Мова:

english

Файл:

PDF, 2.14 MB

english, 2019

Applications of stochastic resonance to machinery fault detection: A review and tutorial

Qiao, Zijian, Lei, Yaguo, Li, Naipeng

Журнал:

Рік:

2019

Мова:

english

Файл:

PDF, 6.05 MB

english, 2019

A Polynomial Kernel Induced Distance Metric to Improve Deep Transfer Learning for Fault Diagnosis of Machines

Yang, Bin, Lei, Yaguo, Jia, Feng, Li, Naipeng, Du, Zhaojun

Журнал:

Рік:

2019

Мова:

english

Файл:

PDF, 2.71 MB

english, 2019

[IEEE 2019 Prognostics and System Health Management Conference (PHM-Qingdao) - Qingdao, China (2019.10.25-2019.10.27)] 2019 Prognostics and System Health Management Conference (PHM-Qingdao) - A Hybrid Transfer Learning Method for Fault Diagnosis of Machinery under Variable Operating Conditions

Du, Zhaojun, Yang, Bin, Lei, Yaguo, Li, Xiwei, Li, Naipeng

Рік:

2019

Файл:

PDF, 1.08 MB

2019

Fault Diagnosis of Rotating Machinery Based on an Adaptive Ensemble Empirical Mode Decomposition

Lei, Yaguo, Li, Naipeng, Lin, Jing, Wang, Sizhe

Журнал:

Sensors

Рік:

2013

Мова:

english

Файл:

PDF, 512 KB

english, 2013

An improved exponential model for predicting remaining useful life of rolling element bearings

Li, Naipeng, Lei, Yaguo, Lin, Jing, Ding, Steven

Журнал:

Рік:

2015

Мова:

english

Файл:

PDF, 4.49 MB

english, 2015

Remaining Useful Life Prediction Based on a General Expression of Stochastic Process Models

Li, Naipeng, Lei, Yaguo, Guo, Liang, Yan, Tao, Lin, Jing

Журнал:

Materials Science and Engineering: A

Рік:

2017

Мова:

english

Файл:

PDF, 1.99 MB

english, 2017

Microstructure and tensile behavior of Fe-8Mn-6Al-0.2C low density steel

Li, Xuan, Song, Renbo, Zhou, Naipeng, Li, Jiajia

Журнал:

Рік:

2017

Мова:

english

Файл:

PDF, 1.14 MB

english, 2017

Dependence of austenite stability and deformation behavior on tempering time in an ultrahigh strength medium Mn TRIP steel

Zhou, Naipeng, Song, Renbo, Li, Xuan, Li, Jiajia

Журнал:

Materials Science and Engineering: A

Рік:

2018

Мова:

english

Файл:

PDF, 2.18 MB

english, 2018

Recurrent convolutional neural network: A new framework for remaining useful life prediction of machinery

Wang, Biao, Lei, Yaguo, Yan, Tao, Li, Naipeng, Guo, Liang

Журнал:

Рік:

2019

Мова:

english

Файл:

PDF, 1.37 MB

english, 2019

Remaining Useful Life Prediction based on a Multi-Sensor Data Fusion Model

Li, Naipeng, Gebraeel, Nagi, Lei, Yaguo, Fang, Xiaolei, Cai, Xiao, Yan, Tao

Журнал:

Рік:

2020

Файл:

PDF, 1.23 MB

2020

Health condition identification of multi-stage planetary gearboxes using a mRVM-based method

Lei, Yaguo, Liu, Zongyao, Wu, Xionghui, Li, Naipeng, Chen, Wu, Lin, Jing

Журнал:

IEEE Transactions on Instrumentation and Measurement

Рік:

2015

Мова:

english

Файл:

PDF, 1.08 MB

english, 2015

[IEEE 2014 IEEE Conference on Prognostics and Health Management (PHM) - Cheney, WA, USA (2014.6.22-2014.6.25)] 2014 International Conference on Prognostics and Health Management - A particle filtering-based approach for remaining useful life predication of rolling element bearings

Naipeng Li,, Yaguo Lei,, Liu, Zongyao, Lin, Jing

Рік:

2014

Мова:

english

Файл:

PDF, 405 KB

english, 2014

[IEEE 2015 Prognostics and System Health Management Conference (PHM) - Beijing, China (2015.10.21-2015.10.23)] 2015 Prognostics and System Health Management Conference (PHM) - A nonlinear degradation model based method for remaining useful life prediction of rolling element bearings

Lei, Yaguo, Li, Naipeng, Feng Jia,, Lin, Jing, Saibo Xing,

Рік:

2015

Мова:

english

Файл:

PDF, 1.68 MB

english, 2015

A New Method Based on Stochastic Process Models for Machine Remaining Useful Life Prediction

Lei, Yaguo, Li, Naipeng, Lin, Jing

Журнал:

Рік:

2016

Мова:

english

Файл:

PDF, 2.71 MB

english, 2016

[IEEE 2017 IEEE International Conference on Prognostics and Health Management (ICPHM) - Dallas, TX, USA (2017.6.19-2017.6.21)] 2017 IEEE International Conference on Prognostics and Health Management (ICPHM) - Machine remaining useful life prediction considering unit-to-unit variability

Li, Naipeng, Lei, Yaguo, Li, Ningbo, Lin, Jing

Рік:

2017

Мова:

english

Файл:

PDF, 315 KB

english, 2017

[IEEE 2017 International Conference on Sensing, Diagnostics, Prognostics and Control (SDPC) - Shanghai (2017.8.16-2017.8.18)] 2017 International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC) - A Distance Metric Learning Based Health Indicator for Health Prognostics of Bearings

Lei, Yaguo, Niu, Shantao, Guo, Liang, Li, Naipeng

Рік:

2017

Мова:

english

Файл:

PDF, 550 KB

english, 2017

[IEEE 2017 Prognostics and System Health Management Conference (PHM-Harbin) - Harbin, China (2017.7.9-2017.7.12)] 2017 Prognostics and System Health Management Conference (PHM-Harbin) - Deep convolution feature learning for health indicator construction of bearings

Guo, Liang, Lei, Yaguo, Li, Naipeng, Xing, Saibo

Рік:

2017

Файл:

PDF, 394 KB

2017

Machinery health indicator construction based on convolutional neural networks considering trend burr

Guo, Liang, Lei, Yaguo, Li, Naipeng, Yan, Tao, Li, Ningbo

Журнал:

Рік:

2018

Мова:

english

Файл:

PDF, 635 KB

english, 2018

A Wiener Process Model-based Method for Remaining Useful Life Prediction Considering Unit-to-Unit Variability

Li, Naipeng, Lei, Yaguo, Yan, Tao, Li, Ningbo, Han, Tianyu

Журнал:

Рік:

2018

Мова:

english

Файл:

PDF, 2.32 MB

english, 2018

Incipient Fault Detection for Rolling Element Bearings under Varying Speed Conditions

Xue, Lang, Li, Naipeng, Lei, Yaguo, Li, Ningbo

Журнал:

Materials

Рік:

2017

Мова:

english

Файл:

PDF, 4.02 MB

english, 2017

Remaining useful life prediction of machinery under time-varying operating conditions based on a two-factor state-space model

Li, Naipeng, Gebraeel, Nagi, Lei, Yaguo, Bian, Linkan, Si, Xiaosheng

Журнал:

Рік:

2019

Файл:

PDF, 2.14 MB

2019

Deep separable convolutional network for remaining useful life prediction of machinery

Wang, Biao, Lei, Yaguo, Li, Naipeng, Yan, Tao

Журнал:

Рік:

2019

Мова:

english

Файл:

PDF, 2.76 MB

english, 2019

Recurrent convolutional neural network: A new framework for remaining useful life prediction of machinery

Wang, Biao, Lei, Yaguo, Yan, Tao, Li, Naipeng, Guo, Liang

Журнал:

Рік:

2019

Файл:

PDF, 1.37 MB

2019

Joint Maintenance and Spare Parts Inventory Optimization for Multi-Unit Systems Considering Imperfect Maintenance Actions

Yan, Tao, Lei, Yaguo, Wang, Biao, Han, Tianyu, Si, Xiaosheng, Li, Naipeng

Журнал:

Рік:

2020

Файл:

PDF, 1.33 MB

2020

Multi-Scale Convolutional Attention Network for Predicting Remaining Useful Life of Machinery

Wang, Biao, Lei, Yaguo, Li, Naipeng, Wang, Wenting

Журнал: