Fault diagnosis of mechanical equipment in high energy consumption industries in China: A review
Y Sun, J Wang, X Wang - Mechanical Systems and Signal Processing, 2023 - Elsevier
Building materials machinery equipment play an important role in the production of cement,
brick and tile, glass and other building materials, which are high energy consumption …
brick and tile, glass and other building materials, which are high energy consumption …
Intelligent diagnosis using continuous wavelet transform and gauss convolutional deep belief network
H Zhao, J Liu, H Chen, J Chen, Y Li… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Bearing fault diagnosis is of significance to ensure the safe and reliable operation of a
motor. Deep learning provides a powerful ability to extract the features of raw data …
motor. Deep learning provides a powerful ability to extract the features of raw data …
Data-driven prognostic scheme for bearings based on a novel health indicator and gated recurrent unit network
The prognosis of bearings is vital for condition-based maintenance of rotating machinery.
This article proposes a systematic prognostic scheme for rolling element bearings. The …
This article proposes a systematic prognostic scheme for rolling element bearings. The …
[HTML][HTML] Technology development and commercial applications of industrial fault diagnosis system: a review
C Liu, A Cichon, G Królczyk, Z Li - The International Journal of Advanced …, 2021 - Springer
Machinery will fail due to complex and tough working conditions. It is necessary to apply
reliable monitoring technology to ensure their safe operation. Condition-based maintenance …
reliable monitoring technology to ensure their safe operation. Condition-based maintenance …
Predicting electrical power output of combined cycle power plants using a novel artificial neural network optimized by electrostatic discharge algorithm
Combined cycle power plants (CCPP) are among the most sophisticated, yet efficient,
systems for producing electrical energy. Hence, simulating their performance has been an …
systems for producing electrical energy. Hence, simulating their performance has been an …
A hybrid generalization network for intelligent fault diagnosis of rotating machinery under unseen working conditions
The data-driven methods in machinery fault diagnosis have become increasingly popular in
the past two decades. However, the wide applications of this scheme are generally …
the past two decades. However, the wide applications of this scheme are generally …
Feature extraction using parameterized multisynchrosqueezing transform
X Li, H Zhao, L Yu, H Chen, W Deng… - IEEE Sensors …, 2022 - ieeexplore.ieee.org
Parametrized time-frequency analysis (PTFA) can effectively improve time-frequency energy
aggregation of non-stationary signal and immunity of cross term interference, but it exists the …
aggregation of non-stationary signal and immunity of cross term interference, but it exists the …
A new tool wear condition monitoring method based on deep learning under small samples
Y Zhou, G Zhi, W Chen, Q Qian, D He, B Sun, W Sun - Measurement, 2022 - Elsevier
Tool wear condition monitoring (TCM) is an important part of machining automation. In
recent years, deep learning (DL) based TCM methods have been widely researched …
recent years, deep learning (DL) based TCM methods have been widely researched …
Context-aware poly (a) signal prediction model via deep spatial–temporal neural networks
Polyadenylation [Poly (A)] is an essential process during messenger RNA (mRNA)
maturation in biological eukaryote systems. Identifying Poly (A) signals (PASs) from the …
maturation in biological eukaryote systems. Identifying Poly (A) signals (PASs) from the …
Intelligent fault diagnosis of worm gearbox based on adaptive CNN using amended gorilla troop optimization with quantum gate mutation strategy
The worm gearbox is a power transmission system that has various applications in
industries. Being vital element of machinery, it becomes necessary to develop a robust fault …
industries. Being vital element of machinery, it becomes necessary to develop a robust fault …