Compound fault diagnosis for rotating machinery: State-of-the-art, challenges, and opportunities
Compound fault, as a primary failure leading to unexpected downtime of rotating machinery,
dramatically increases the difficulty in fault diagnosis. To deal with the difficulty encountered …
dramatically increases the difficulty in fault diagnosis. To deal with the difficulty encountered …
Anti‐noise diesel engine misfire diagnosis using a multi‐scale CNN‐LSTM neural network with denoising module
Currently, accuracy of existing diesel engine fault diagnosis methods under strong noise
and generalisation performance between different noise levels are still limited. A novel multi …
and generalisation performance between different noise levels are still limited. A novel multi …
A novel LSTM-autoencoder and enhanced transformer-based detection method for shield machine cutterhead clogging
CJ Qin, RH Wu, GQ Huang, JF Tao, CL Liu - Science China Technological …, 2023 - Springer
Shield tunneling machines are paramount underground engineering equipment and play a
key role in tunnel construction. During the shield construction process, the “mud cake” …
key role in tunnel construction. During the shield construction process, the “mud cake” …
A novel attentional deep neural network-based assessment method for ECG quality
ECG quality assessment is of great significance to reduce false alarms in automatic
arrhythmia and other cardiovascular diseases diagnoses and reduce the workload of …
arrhythmia and other cardiovascular diseases diagnoses and reduce the workload of …
An elastic expandable fault diagnosis method of three-phase motors using continual learning for class-added sample accumulations
A Ding, Y Qin, B Wang, X Cheng… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Continual learning is promising in intelligent fault diagnosis of three-phase motors, which
allows diagnosis networks to increase diagnosable fault classes without tedious retraining …
allows diagnosis networks to increase diagnosable fault classes without tedious retraining …
A novel deep wavelet convolutional neural network for actual ecg signal denoising
Recently, more than 80% of sudden cardiac death is caused by arrhythmia, whose
incidence has increased rapidly. In the actual wearable device acquisition process, ECG …
incidence has increased rapidly. In the actual wearable device acquisition process, ECG …
[HTML][HTML] Geological information prediction for shield machine using an enhanced multi-head self-attention convolution neural network with two-stage feature extraction
Due to the closed working environment of shield machines, the construction personnel
cannot observe the construction geological environment, which seriously restricts the safety …
cannot observe the construction geological environment, which seriously restricts the safety …
SKND-TSACNN: A novel time-scale adaptive CNN framework for fault diagnosis of rotating machinery
Z Yu, C Zhang, J Liu, C Deng - Knowledge-Based Systems, 2023 - Elsevier
Recently, deep learning models represented by convolutional neural networks (CNN) have
played an increasingly important role in rotating machinery fault diagnosis (FD). However …
played an increasingly important role in rotating machinery fault diagnosis (FD). However …
Augmentation-based discriminative meta-learning for cross-machine few-shot fault diagnosis
Deep learning methods have demonstrated promising performance in fault diagnosis tasks.
Although the scarcity of data in industrial scenarios limits the practical application of such …
Although the scarcity of data in industrial scenarios limits the practical application of such …
A roller state-based fault diagnosis method for tunnel boring machine main bearing using two-stream CNN with multichannel detrending inputs
As the key component of the tunnel boring machine (TBM), the main bearing supports the
cutter head as it rotates and breaks rock. It is commonly operated in low-speed, heavy-load …
cutter head as it rotates and breaks rock. It is commonly operated in low-speed, heavy-load …