Applications of machine learning to machine fault diagnosis: A review and roadmap
Intelligent fault diagnosis (IFD) refers to applications of machine learning theories to
machine fault diagnosis. This is a promising way to release the contribution from human …
machine fault diagnosis. This is a promising way to release the contribution from human …
Construction of health indicators for condition monitoring of rotating machinery: A review of the research
The condition monitoring (CM) of rotating machinery (RM) is an essential operation for
improving the reliability of mechanical systems. For this purpose, an efficient CM method that …
improving the reliability of mechanical systems. For this purpose, an efficient CM method that …
[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 …
An integrated multitasking intelligent bearing fault diagnosis scheme based on representation learning under imbalanced sample condition
Accurate bearing fault diagnosis is of great significance of the safety and reliability of rotary
mechanical system. In practice, the sample proportion between faulty data and healthy data …
mechanical system. In practice, the sample proportion between faulty data and healthy data …
An explainable artificial intelligence approach for unsupervised fault detection and diagnosis in rotating machinery
The monitoring of rotating machinery is an essential task in today's production processes.
Currently, several machine learning and deep learning-based modules have achieved …
Currently, several machine learning and deep learning-based modules have achieved …
Machinery health prognostics: A systematic review from data acquisition to RUL prediction
Machinery prognostics is one of the major tasks in condition based maintenance (CBM),
which aims to predict the remaining useful life (RUL) of machinery based on condition …
which aims to predict the remaining useful life (RUL) of machinery based on condition …
Deep learning-based remaining useful life estimation of bearings using multi-scale feature extraction
Accurate evaluation of machine degradation during long-time operation is of great
importance. With the rapid development of modern industries, physical model is becoming …
importance. With the rapid development of modern industries, physical model is becoming …
Optimization of state-of-the-art fuzzy-metaheuristic ANFIS-based machine learning models for flood susceptibility prediction mapping in the Middle Ganga Plain, India
This study is an attempt to quantitatively test and compare novel advanced-machine
learning algorithms in terms of their performance in achieving the goal of predicting flood …
learning algorithms in terms of their performance in achieving the goal of predicting flood …
Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data
Aiming to promptly process the massive fault data and automatically provide accurate
diagnosis results, numerous studies have been conducted on intelligent fault diagnosis of …
diagnosis results, numerous studies have been conducted on intelligent fault diagnosis of …
An intelligent fault diagnosis method using unsupervised feature learning towards mechanical big data
Y Lei, F Jia, J Lin, S Xing… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
Intelligent fault diagnosis is a promising tool to deal with mechanical big data due to its
ability in rapidly and efficiently processing collected signals and providing accurate …
ability in rapidly and efficiently processing collected signals and providing accurate …