[HTML][HTML] Intelligent condition monitoring method for bearing faults from highly compressed measurements using sparse over-complete features
Condition classification of rolling element bearings in rotating machines is important to
prevent the breakdown of industrial machinery. A considerable amount of literature has …
prevent the breakdown of industrial machinery. A considerable amount of literature has …
CSWGAN-GP: A new method for bearing fault diagnosis under imbalanced condition
X Gu, Y Yu, L Guo, H Gao, M Luo - Measurement, 2023 - Elsevier
Most intelligent bearing fault diagnosis methods are conducted with balanced datasets,
which is not in line with the reality of industry. Suffering from this problem, intelligent …
which is not in line with the reality of industry. Suffering from this problem, intelligent …
Bearing fault diagnosis using piecewise aggregate approximation and complete ensemble empirical mode decomposition with adaptive noise
L Hu, L Wang, Y Chen, N Hu, Y Jiang - Sensors, 2022 - mdpi.com
Complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN)
effectively separates the fault vibration signals of rolling bearings and improves the …
effectively separates the fault vibration signals of rolling bearings and improves the …
Multiscale reduction clustering of vibration signals for unsupervised diagnosis of machine faults
Fault diagnosis is of great importance for the intelligent health management of mechanical
systems. For engineering applications, it is very difficult to collect and label vibration signals …
systems. For engineering applications, it is very difficult to collect and label vibration signals …
Compressive sampling and feature ranking framework for bearing fault classification with vibration signals
Failures of rolling element bearings are amongst the main causes of machines breakdowns.
To prevent such breakdowns, bearing health monitoring is performed by collecting data from …
To prevent such breakdowns, bearing health monitoring is performed by collecting data from …
A deep learning framework for adaptive compressive sensing of high‐speed train vibration responses
Onboard monitoring plays an important role in real‐time condition assessment of rail
systems. However, the data amount is typically tremendous due to the high sampling rate …
systems. However, the data amount is typically tremendous due to the high sampling rate …
A new fault diagnosis method based on convolutional neural network and compressive sensing
Y Ma, X Jia, H Bai, G Liu, G Wang, C Guo… - Journal of Mechanical …, 2019 - Springer
Compressive sensing is an efficient machinery monitoring framework, which just needs to
sample and store a small amount of observed signal. However, traditional reconstruction …
sample and store a small amount of observed signal. However, traditional reconstruction …
Design and implementation of acoustic sensing system for online early fault detection in industrial fans
Industrial fans play a critical role in manufacturing facilities, and a sudden shutdown of
critical fans can cause significant disruptions. Ensuring early, effective, and accurate …
critical fans can cause significant disruptions. Ensuring early, effective, and accurate …
Intrinsic Dimension Estimation-Based Feature Selection and Multinomial Logistic Regression for Classification of Bearing Faults Using Compressively Sampled …
As failures of rolling bearings lead to major failures in rotating machines, recent vibration-
based rolling bearing fault diagnosis techniques are focused on obtaining useful fault …
based rolling bearing fault diagnosis techniques are focused on obtaining useful fault …
Segmentation-oriented compressed sensing for efficient impact damage detection on CFRP materials
The emerging task-oriented compressed sensing (CS) provides a possibility to revolutionize
traditional separate sensing-processing models by jointly considering task with data and …
traditional separate sensing-processing models by jointly considering task with data and …