Bearing fault detection and diagnosis using case western reserve university dataset with deep learning approaches: A review
A smart factory is a highly digitized and connected production facility that relies on smart
manufacturing. Additionally, artificial intelligence is the core technology of smart factories …
manufacturing. Additionally, artificial intelligence is the core technology of smart factories …
[HTML][HTML] Fault diagnosis in industrial rotating equipment based on permutation entropy, signal processing and multi-output neuro-fuzzy classifier
Rotating equipment is considered as a key component in several industrial sectors. In fact,
the continuous operation of many industrial machines such as sub-sea pumps and gas …
the continuous operation of many industrial machines such as sub-sea pumps and gas …
Detection of keyhole pore formations in laser powder-bed fusion using acoustic process monitoring measurements
In-situ process monitoring of additively manufactured parts has become a topic of increasing
interest to the manufacturing community. In this work, acoustic measurements recorded …
interest to the manufacturing community. In this work, acoustic measurements recorded …
A novel bearing fault diagnosis model integrated permutation entropy, ensemble empirical mode decomposition and optimized SVM
X Zhang, Y Liang, J Zhou - Measurement, 2015 - Elsevier
This paper presents a novel hybrid model for fault detection and classification of motor
bearing. In the proposed model, permutation entropy (PE) of the vibration signal is …
bearing. In the proposed model, permutation entropy (PE) of the vibration signal is …
Fault detection and diagnosis of marine diesel engines: A systematic review
Y Lv, X Yang, Y Li, J Liu, S Li - Ocean Engineering, 2024 - Elsevier
Marine diesel engines play a pivotal role in ensuring the smooth operation of maritime
vessels. However, given the rigorous operational conditions and the natural wear and tear of …
vessels. However, given the rigorous operational conditions and the natural wear and tear of …
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 comparative study between Empirical Wavelet Transforms and Empirical Mode Decomposition Methods: Application to bearing defect diagnosis
Abstract The Ensemble Empirical Mode Decomposition (EEMD) is a noise assisted method
that may sometimes provide a significant improvement on Empirical Mode Decomposition …
that may sometimes provide a significant improvement on Empirical Mode Decomposition …
An adaptive multiscale fully convolutional network for bearing fault diagnosis under noisy environments
F Li, L Wang, D Wang, J Wu, H Zhao - Measurement, 2023 - Elsevier
Intelligent algorithms based on convolutional neural network (CNN) has demonstrated
remarkable potential in diagnosing bearing faults. However, Accurate and robust fault …
remarkable potential in diagnosing bearing faults. However, Accurate and robust fault …
A neural network compression method based on knowledge-distillation and parameter quantization for the bearing fault diagnosis
Condition monitoring and fault diagnosis have been critical for the optimal scheduling of
machines, improving the system reliability and the reducing maintenance cost. In recent …
machines, improving the system reliability and the reducing maintenance cost. In recent …
DTCNNMI: A deep twin convolutional neural networks with multi-domain inputs for strongly noisy diesel engine misfire detection
Although machine learning-based intelligent detection methods have made many
achievements for diesel engine misfire diagnosis, they suffer from a certain degree of …
achievements for diesel engine misfire diagnosis, they suffer from a certain degree of …