Macroscopic–microscopic attention in LSTM networks based on fusion features for gear remaining life prediction
In the mechanical transmission system, the gear is one of the most widely used transmission
components. The failure of the gear will cause serious accidents and huge economic loss …
components. The failure of the gear will cause serious accidents and huge economic loss …
ReLTanh: An activation function with vanishing gradient resistance for SAE-based DNNs and its application to rotating machinery fault diagnosis
Tanh is a sigmoidal activation function that suffers from vanishing gradient problem, so
researchers have proposed some alternative functions including rectified linear unit (ReLU) …
researchers have proposed some alternative functions including rectified linear unit (ReLU) …
Long short-term memory neural network with weight amplification and its application into gear remaining useful life prediction
As an important component of industrial equipment, once gears have failures, they may
cause serious catastrophes. Thus, the prediction of gear remaining life is of great …
cause serious catastrophes. Thus, the prediction of gear remaining life is of great …
Long-term gear life prediction based on ordered neurons LSTM neural networks
Gear failure may affect the operation of mechanical equipment, and even cause the
catastrophic break of machine and even casualties. Thus, the remaining useful life (RUL) …
catastrophic break of machine and even casualties. Thus, the remaining useful life (RUL) …
LSTM networks based on attention ordered neurons for gear remaining life prediction
Gear is a commonly-used rotating part in industry, it is of great significance to predict its
failure in advance, which is helpful to maintain the health of the whole machine. Firstly, the …
failure in advance, which is helpful to maintain the health of the whole machine. Firstly, the …
A two-level adaptive chirp mode decomposition method for the railway wheel flat detection under variable-speed conditions
Wheel flat, as a common defect of railway vehicles, can cause large impact forces on both
the vehicle and infrastructure components and thus seriously hinder the vehicle running …
the vehicle and infrastructure components and thus seriously hinder the vehicle running …
Harmonics signal feature extraction techniques: A review
Harmonic estimation is essential for mitigating or suppressing harmonic distortions in power
systems. The most important idea is that spectrum analysis, waveform estimation, harmonic …
systems. The most important idea is that spectrum analysis, waveform estimation, harmonic …
Sparse elitist group lasso denoising in frequency domain for bearing fault diagnosis
The fault-induced impulse responses of localized bearing fault are usually interfered by the
background noise and other harmonic components. They are strongly coupled together and …
background noise and other harmonic components. They are strongly coupled together and …
Manifold sensing-based convolution sparse self-learning for defective bearing morphological feature extraction
Q Li, X Ding, Q He, W Huang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The transient features caused by a local fault are of vital importance for bearing fault
diagnosis in an intelligent industry. Due to the uncertainty of fault forms and nonstationarity …
diagnosis in an intelligent industry. Due to the uncertainty of fault forms and nonstationarity …
A fault dynamic model of high-speed angular contact ball bearings
Y Qin, C Li, F Cao, H Chen - Mechanism and Machine Theory, 2020 - Elsevier
Angular contact ball bearings (ACBBs) are widely used in rotary machines especially in high-
speed rotating machines because of their excellent properties. However, the traditional …
speed rotating machines because of their excellent properties. However, the traditional …