A review of the application of deep learning in intelligent fault diagnosis of rotating machinery
Z Zhu, Y Lei, G Qi, Y Chai, N Mazur, Y An, X Huang - Measurement, 2023 - Elsevier
With the rapid development of industry, fault diagnosis plays a more and more important role
in maintaining the health of equipment and ensuring the safe operation of equipment. Due to …
in maintaining the health of equipment and ensuring the safe operation of equipment. Due to …
Mel frequency cepstral coefficient and its applications: A review
ZK Abdul, AK Al-Talabani - IEEE Access, 2022 - ieeexplore.ieee.org
Feature extraction and representation has significant impact on the performance of any
machine learning method. Mel Frequency Cepstrum Coefficient (MFCC) is designed to …
machine learning method. Mel Frequency Cepstrum Coefficient (MFCC) is designed to …
Fault detection of the harmonic reducer based on CNN-LSTM with a novel denoising algorithm
The harmonic reducer is a key component of the industrial robot. Its reliability has significant
influence on the consecutive operation of the industrial robot. However, its failure rate is high …
influence on the consecutive operation of the industrial robot. However, its failure rate is high …
[HTML][HTML] Intelligent fault diagnosis of helical gearboxes with compressive sensing based non-contact measurements
Helical gearboxes play a critical role in power transmission of industrial applications. They
are vulnerable to various faults due to long-term and heavy-duty operating conditions. To …
are vulnerable to various faults due to long-term and heavy-duty operating conditions. To …
A hybrid LSTM-KLD approach to condition monitoring of operational wind turbines
With the increasing installation of the wind turbines both onshore and offshore, condition
monitoring technologies and systems have become increasingly important in order to …
monitoring technologies and systems have become increasingly important in order to …
Fault diagnosis of various rotating equipment using machine learning approaches–A review
S Manikandan, K Duraivelu - Proceedings of the Institution of …, 2021 - journals.sagepub.com
Fault diagnosis of various rotating equipment plays a significant role in industries as it
guarantees safety, reliability and prevents breakdown and loss of any source of energy …
guarantees safety, reliability and prevents breakdown and loss of any source of energy …
Parallel multi-fusion convolutional neural networks based fault diagnosis of rotating machinery under noisy environments
Fault diagnosis has a great significance in preventing serious failures of rotating machinery
and avoiding huge economic losses. The performance of the existing fault diagnosis …
and avoiding huge economic losses. The performance of the existing fault diagnosis …
State of the art on vibration signal processing towards data‐driven gear fault diagnosis
S Zhang, J Zhou, E Wang, H Zhang… - IET Collaborative …, 2022 - Wiley Online Library
Gear fault diagnosis (GFD) based on vibration signals is a popular research topic in industry
and academia. This paper provides a comprehensive summary and systematic review of …
and academia. This paper provides a comprehensive summary and systematic review of …
DWT-LSTM-based fault diagnosis of rolling bearings with multi-sensors
K Gu, Y Zhang, X Liu, H Li, M Ren - Electronics, 2021 - mdpi.com
Bearings are widely used in many steam turbine generator sets and other large rotating
equipment. With the rapid development of contemporary industry, there is a great number of …
equipment. With the rapid development of contemporary industry, there is a great number of …
An advanced operation mode with product-service system using lifecycle big data and deep learning
As a successful business strategy for enhancing environmental sustainability and
decreasing the natural resource consumption of societies, the product-service system (PSS) …
decreasing the natural resource consumption of societies, the product-service system (PSS) …