[HTML][HTML] Semi-supervised learning for industrial fault detection and diagnosis: A systemic review
JM Ramírez-Sanz, JA Maestro-Prieto… - ISA transactions, 2023 - Elsevier
Abstract The automation of Fault Detection and Diagnosis (FDD) is a central task for many
industries today. A myriad of methods are in use, although the most recent leading …
industries today. A myriad of methods are in use, although the most recent leading …
A label description space embedded model for zero-shot intelligent diagnosis of mechanical compound faults
It has always been an issue of significance to diagnose compound faults of machines.
Existing intelligent diagnosis methods have to be trained by sufficient data of each …
Existing intelligent diagnosis methods have to be trained by sufficient data of each …
Self-supervised signal representation learning for machinery fault diagnosis under limited annotation data
Recently, convolutional neural networks (CNNs) have achieved remarkable success in
machinery fault diagnosis. However, these methods usually require mass of manually …
machinery fault diagnosis. However, these methods usually require mass of manually …
Intelligent fault diagnosis of bevel gearboxes using semi-supervised probability support matrix machine and infrared imaging
Fault diagnosis is of great significance to ensure the reliability and safety of complex bevel
gearbox systems. Most existing intelligent fault diagnosis approaches of bevel gearboxes …
gearbox systems. Most existing intelligent fault diagnosis approaches of bevel gearboxes …
Simulation data driven weakly supervised adversarial domain adaptation approach for intelligent cross-machine fault diagnosis
In current research works, a number of intelligent fault diagnosis methods have been
proposed with the assistance of domain adaptation approach, which attempt to distinguish …
proposed with the assistance of domain adaptation approach, which attempt to distinguish …
Semi-supervised fault diagnosis of machinery using LPS-DGAT under speed fluctuation and extremely low labeled rates
Recent research in semi-supervised fault diagnosis of machinery based on graph neural
networks (GNNs) still has some problems, such as insufficient label information mining …
networks (GNNs) still has some problems, such as insufficient label information mining …
A chatter detection method in milling of thin-walled TC4 alloy workpiece based on auto-encoding and hybrid clustering
Chatter is a typical fault in milling, which is a self-excited vibration. Chatter can be diagnosed
by using several methods, such as Delay Differential Equation (DDE) modelling methods …
by using several methods, such as Delay Differential Equation (DDE) modelling methods …
Unsupervised machine fault diagnosis for noisy domain adaptation using marginal denoising autoencoder based on acoustic signals
Recently, with the desperate demand for data-driven deep learning methods in practical
industrial applications, increasing popularity of deep learning methods for machine fault …
industrial applications, increasing popularity of deep learning methods for machine fault …
[PDF][PDF] 深度嵌入关系空间下齿轮箱标记样本扩充及其半监督故障诊断方法
吕枫， 王义， 阮胡林， 秦毅， 王平 - 仪器仪表学报, 2023 - femt.cnjournals.com
针对只有少量标记样本的情况下, 传统的基于深度学习的齿轮箱故障诊断方法训练出来的深度
模型泛化能力差并且容易发生过拟合的问题, 提出了一种基于深度嵌入关系空间下齿轮箱标记 …
模型泛化能力差并且容易发生过拟合的问题, 提出了一种基于深度嵌入关系空间下齿轮箱标记 …
Feature-level consistency regularized Semi-supervised scheme with data augmentation for intelligent fault diagnosis under small samples
T Zhang, C Li, J Chen, S He, Z Zhou - Mechanical Systems and Signal …, 2023 - Elsevier
Intelligent fault diagnosis based on machine learning has yielded a wealth of research
results. However, fault diagnosis under small samples is still a challenging problem due to …
results. However, fault diagnosis under small samples is still a challenging problem due to …