Towards Zero Defect Manufacturing paradigm: A review of the state-of-the-art methods and open challenges
Abstract Nowadays, Internet-of-Things (IoT), big data, and cloud computing technologies
allow increasing the throughput and quality of manufacturing systems, bringing to the rise of …
allow increasing the throughput and quality of manufacturing systems, bringing to the rise of …
[PDF][PDF] Fault analysis of wind power rolling bearing based on EMD feature extraction
D Meng, H Wang, S Yang, Z Lv, Z Hu… - … -Computer Modeling in …, 2022 - cdn.techscience.cn
In a wind turbine, the rolling bearing is the critical component. However, it has a high failure
rate. Therefore, the failure analysis and fault diagnosis of wind power rolling bearings are …
rate. Therefore, the failure analysis and fault diagnosis of wind power rolling bearings are …
A high-impedance fault detection method for distribution systems based on empirical wavelet transform and differential faulty energy
High-impedance faults (HIFs) pose the greatest challenge for distribution system protection,
especially for microgrids and distribution networks with distributed generators (DGs) that …
especially for microgrids and distribution networks with distributed generators (DGs) that …
Entropy measures in machine fault diagnosis: Insights and applications
Entropy, as a complexity measure, has been widely applied for time series analysis. One
preeminent example is the design of machine condition monitoring and industrial fault …
preeminent example is the design of machine condition monitoring and industrial fault …
Rolling bearing fault diagnosis based on convolutional neural network and support vector machine
L Yuan, D Lian, X Kang, Y Chen, K Zhai - IEEE Access, 2020 - ieeexplore.ieee.org
Rolling bearings are one of the essential components in rotating machinery. Efficient
bearing fault diagnosis is necessary to ensure the regular operation of the mechanical …
bearing fault diagnosis is necessary to ensure the regular operation of the mechanical …
Fault diagnosis and investigation techniques for induction motor
Induction motors are the most popular machines in industrial drive and power conversion
systems. This popularity makes the recent industries impose reliable and continuous work …
systems. This popularity makes the recent industries impose reliable and continuous work …
Multivariate feature extraction based supervised machine learning for fault detection and diagnosis in photovoltaic systems
Fault detection and diagnosis (FDD) in the photovoltaic (PV) array has become a challenge
due to the magnitudes of the faults, the presence of maximum power point trackers, non …
due to the magnitudes of the faults, the presence of maximum power point trackers, non …
Fault diagnosis for rolling bearing using a hybrid hierarchical method based on scale-variable dispersion entropy and parametric t-SNE algorithm
W Jiang, Y Xu, Z Chen, N Zhang, J Zhou - Measurement, 2022 - Elsevier
Accurate and efficient fault diagnosis for rolling bearing is essential to ensure the reliable
and safe operation of mechanical equipment. In this paper, a hybrid hierarchical fault …
and safe operation of mechanical equipment. In this paper, a hybrid hierarchical fault …
Rolling bearing fault diagnosis based on CEEMDAN and refined composite multiscale fuzzy entropy
S Gao, Q Wang, Y Zhang - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Considering the nonlinear and nonstationary characteristics of rolling bearing vibration
signals, we propose a rolling bearing fault diagnosis method based on complete ensemble …
signals, we propose a rolling bearing fault diagnosis method based on complete ensemble …
Bearing fault detection and recognition methodology based on weighted multiscale entropy approach
In the present study, a new bearing fault detection and recognition methodology is proposed
based on complementary ensemble empirical mode decomposition method (CEEMD) and a …
based on complementary ensemble empirical mode decomposition method (CEEMD) and a …