Deep-convolution-based LSTM network for remaining useful life prediction
Accurate prediction of remaining useful life (RUL) has been a critical and challenging
problem in the field of prognostics and health management (PHM), which aims to make …
problem in the field of prognostics and health management (PHM), which aims to make …
Modified deep autoencoder driven by multisource parameters for fault transfer prognosis of aeroengine
The existing fault prognosis techniques of aeroengine mostly focus on a single monitoring
parameter under stable condition, and have low adaptability to new prognosis scenes. To …
parameter under stable condition, and have low adaptability to new prognosis scenes. To …
Normalized conditional variational auto-encoder with adaptive focal loss for imbalanced fault diagnosis of bearing-rotor system
The distribution of the health data monitored from mechanical system in the industries is
class imbalanced mainly. The amount of monitoring data for the normal condition is far more …
class imbalanced mainly. The amount of monitoring data for the normal condition is far more …
Twin robust matrix machine for intelligent fault identification of outlier samples in roller bearing
In the industrial processes, the intelligent fault diagnosis related to signal analysis and
pattern recognition is an important step to ensure the health of mechanical equipment. A …
pattern recognition is an important step to ensure the health of mechanical equipment. A …
Feature-level SMOTE: Augmenting fault samples in learnable feature space for imbalanced fault diagnosis of gas turbines
A challenge in gas turbine fault diagnosis is that labeled fault samples are relatively rare and
much fewer than normal samples. Conventional data augmentation techniques generate …
much fewer than normal samples. Conventional data augmentation techniques generate …
A deep coupled network for health state assessment of cutting tools based on fusion of multisensory signals
The cutting tool is a key part of a machine system, which plays an important role in modern
manufacturing systems. To avoid an unexpected tool failure, it is necessary to carry out …
manufacturing systems. To avoid an unexpected tool failure, it is necessary to carry out …
Non-parallel least squares support matrix machine for rolling bearing fault diagnosis
X Li, Y Yang, H Pan, J Cheng, J Cheng - Mechanism and Machine Theory, 2020 - Elsevier
For rolling bearing fault classification, the input samples can be naturally expressed as two-
dimensional matrices in some cases, such as time-frequency grayscale diagram and …
dimensional matrices in some cases, such as time-frequency grayscale diagram and …
Deep wavelet sequence-based gated recurrent units for the prognosis of rotating machinery
Prognostics and health management (PHM) is an emerging technique which aims to
improve the reliability and safety of machinery systems. Remaining useful life (RUL) …
improve the reliability and safety of machinery systems. Remaining useful life (RUL) …
基于深度置信网络的多模态过程故障评估方法及应用
张凯， 杨朋澄， 彭开香， 陈志文 - 自动化学报, 2024 - aas.net.cn
传统的多模态过程故障等级评估方法对模态之间的共性特征考虑较少, 导致当被评估模态故障
信息不充分时, 评估的准确性较低. 针对此问题, 首先, 提出一种共性–个性深度置信网络 …
信息不充分时, 评估的准确性较低. 针对此问题, 首先, 提出一种共性–个性深度置信网络 …
Sparsity preserving projection aided baselined hyperdisk modeling for interpretable machine health monitoring
Geometric representation optimization models have been widely introduced for machine
health monitoring. Nevertheless, their extracted features for machine fault diagnosis lack …
health monitoring. Nevertheless, their extracted features for machine fault diagnosis lack …