A comprehensive review on signal-based and model-based condition monitoring of wind turbines: Fault diagnosis and lifetime prognosis
Wind turbines play an increasingly important role in renewable power generation. To ensure
the efficient production and financial viability of wind power, it is crucial to maintain wind …
the efficient production and financial viability of wind power, it is crucial to maintain wind …
Bearing fault diagnosis via generalized logarithm sparse regularization
Bearing fault is the most common causes of rotating machinery failure. Therefore, accurate
bearing fault identification technique is of tremendous significance. Vibration monitoring has …
bearing fault identification technique is of tremendous significance. Vibration monitoring has …
Bayesian optimization and channel-fusion-based convolutional autoencoder network for fault diagnosis of rotating machinery
L Zou, KJ Zhuang, A Zhou, J Hu - Engineering Structures, 2023 - Elsevier
Deep learning methods are essential for the application of data driven technologies on fault
diagnosis of rotating machinery. However, the generalization and performance of deep …
diagnosis of rotating machinery. However, the generalization and performance of deep …
Detection of mechanical failures in industrial machines using overlapping acoustic anomalies: A systematic literature review
One of the most important strategies for preventative factory maintenance is anomaly
detection without the need for dedicated sensors for each industrial unit. The implementation …
detection without the need for dedicated sensors for each industrial unit. The implementation …
A comparative experimental study of vibration and acoustic emission on fault diagnosis of low-speed bearing
L Tang, X Wu, D Wang, X Liu - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Traditional bearing fault diagnosis is mainly based on periodic feature extraction from
bearing fault pulses. However, the diagnostic accuracy was limited due to the absence of …
bearing fault pulses. However, the diagnostic accuracy was limited due to the absence of …
Sensor data modeling and model frequency analysis for detecting cutting tool anomalies in machining
Tool condition monitoring (TCM) in advanced manufacturing is concerned with cutting tool
operational status monitoring and damage diagnosis. In the present study, an innovative …
operational status monitoring and damage diagnosis. In the present study, an innovative …
[HTML][HTML] Wind turbine blade bearing fault detection with Bayesian and Adaptive Kalman Augmented Lagrangian Algorithm
As a critically supporting and rotational component for wind turbines, blade bearings need
special health monitoring for safe operation in actual industrial conditions. One of the main …
special health monitoring for safe operation in actual industrial conditions. One of the main …
Multi-domain bearing fault diagnosis using support vector machine
RK Mishra, A Choudhary, AR Mohanty… - 2021 IEEE 4th …, 2021 - ieeexplore.ieee.org
Faults in rolling element bearings are the main cause of rotating machine failure. Locating
and isolating the faults has become a critical concern for the stable operation of rotating …
and isolating the faults has become a critical concern for the stable operation of rotating …
A roller state-based fault diagnosis method for tunnel boring machine main bearing using two-stream CNN with multichannel detrending inputs
As the key component of the tunnel boring machine (TBM), the main bearing supports the
cutter head as it rotates and breaks rock. It is commonly operated in low-speed, heavy-load …
cutter head as it rotates and breaks rock. It is commonly operated in low-speed, heavy-load …
[HTML][HTML] A rolling-horizon cleaning recommendation system for dust removal of industrial PV panels
Periodic cleaning of photovoltaic (PV) panels, such as every three months, is a common
industry practice. However, this fixed period may not be optimal for maximizing the profit of a …
industry practice. However, this fixed period may not be optimal for maximizing the profit of a …