A comprehensive review of digital twin—part 1: modeling and twinning enabling technologies
As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented
attention because of its promise to further optimize process design, quality control, health …
attention because of its promise to further optimize process design, quality control, health …
A systematic review of deep transfer learning for machinery fault diagnosis
With the popularization of the intelligent manufacturing, much attention has been paid in
such intelligent computing methods as deep learning ones for machinery fault diagnosis …
such intelligent computing methods as deep learning ones for machinery fault diagnosis …
Prognostics and Health Management (PHM): Where are we and where do we (need to) go in theory and practice
E Zio - Reliability Engineering & System Safety, 2022 - Elsevier
We are performing the digital transition of industry, living the 4th industrial revolution,
building a new World in which the digital, physical and human dimensions are interrelated in …
building a new World in which the digital, physical and human dimensions are interrelated in …
[PDF][PDF] XJTU-SY 滚动轴承加速寿命试验数据集解读
雷亚国, 韩天宇, 王彪, 李乃鹏, 闫涛, 杨军 - 机械工程学报, 2019 - qikan.cmes.org
预测与健康管理对保障机械装备安全服役, 提高生产效率, 增加经济效益至关重要.
高质量的全寿命周期数据是预测与健康管理领域的基础性资源, 这些数据承载着反映装备服役 …
高质量的全寿命周期数据是预测与健康管理领域的基础性资源, 这些数据承载着反映装备服役 …
[HTML][HTML] Predictive maintenance enabled by machine learning: Use cases and challenges in the automotive industry
A Theissler, J Pérez-Velázquez, M Kettelgerdes… - Reliability engineering & …, 2021 - Elsevier
Recent developments in maintenance modelling fueled by data-based approaches such as
machine learning (ML), have enabled a broad range of applications. In the automotive …
machine learning (ML), have enabled a broad range of applications. In the automotive …
Machine learning for reliability engineering and safety applications: Review of current status and future opportunities
Abstract Machine learning (ML) pervades an increasing number of academic disciplines and
industries. Its impact is profound, and several fields have been fundamentally altered by it …
industries. Its impact is profound, and several fields have been fundamentally altered by it …
Federated learning for machinery fault diagnosis with dynamic validation and self-supervision
Intelligent data-driven machinery fault diagnosis methods have been successfully and
popularly developed in the past years. While promising diagnostic performance has been …
popularly developed in the past years. While promising diagnostic performance has been …
Intelligent fault diagnosis of rolling bearings based on normalized CNN considering data imbalance and variable working conditions
Intelligent fault detection and diagnosis, as an important approach, play a crucial role in
ensuring the stable, reliable and safe operation of rolling bearings, which is one of the most …
ensuring the stable, reliable and safe operation of rolling bearings, which is one of the most …
A comprehensive review on convolutional neural network in machine fault diagnosis
With the rapid development of manufacturing industry, machine fault diagnosis has become
increasingly significant to ensure safe equipment operation and production. Consequently …
increasingly significant to ensure safe equipment operation and production. Consequently …
Deep learning for prognostics and health management: State of the art, challenges, and opportunities
B Rezaeianjouybari, Y Shang - Measurement, 2020 - Elsevier
Improving the reliability of engineered systems is a crucial problem in many applications in
various engineering fields, such as aerospace, nuclear energy, and water declination …
various engineering fields, such as aerospace, nuclear energy, and water declination …