Tacholess speed estimation in order tracking: A review with application to rotating machine fault diagnosis

S Lu, R Yan, Y Liu, Q Wang - IEEE Transactions on …, 2019‏ - ieeexplore.ieee.org
Order tracking (OT), which is realized by signal sampling in equal-angle increment
according to the measured rotating speed, is a powerful technique for rotating machine fault …

Condition monitoring and fault diagnosis of induction motor

SK Gundewar, PV Kane - Journal of Vibration Engineering & Technologies, 2021‏ - Springer
Background An induction motor is at the heart of every rotating machine and hence it is a
very vital component. Almost in every industry, around 90% of the machines apply an …

Wavelet transform for rotary machine fault diagnosis: 10 years revisited

R Yan, Z Shang, H Xu, J Wen, Z Zhao, X Chen… - Mechanical systems and …, 2023‏ - Elsevier
As a multi-resolution analysis method rooted rigorously in mathematics, wavelet transform
(WT) has shown its great potential in rotary machine fault diagnosis, characterized by …

An improved ant colony optimization algorithm based on hybrid strategies for scheduling problem

W Deng, J Xu, H Zhao - IEEE access, 2019‏ - ieeexplore.ieee.org
In this paper, an improved ant colony optimization (ICMPACO) algorithm based on the multi-
population strategy, co-evolution mechanism, pheromone updating strategy, and …

Machine fault detection using a hybrid CNN-LSTM attention-based model

A Borré, LO Seman, E Camponogara, SF Stefenon… - Sensors, 2023‏ - mdpi.com
The predictive maintenance of electrical machines is a critical issue for companies, as it can
greatly reduce maintenance costs, increase efficiency, and minimize downtime. In this …

Two-layer fuzzy multiple random forest for speech emotion recognition in human-robot interaction

L Chen, W Su, Y Feng, M Wu, J She, K Hirota - Information Sciences, 2020‏ - Elsevier
The two-layer fuzzy multiple random forest (TLFMRF) is proposed for speech emotion
recognition. When recognizing speech emotion, there are usually some problems. One is …

Multiscale symbolic fuzzy entropy: An entropy denoising method for weak feature extraction of rotating machinery

Y Li, S Wang, Y Yang, Z Deng - Mechanical Systems and Signal …, 2022‏ - Elsevier
The entropy-based method has been demonstrated to be an effective approach to extract
the fault features by estimating the complexity of signals, but how to remove the strong …

Fault diagnosis method based on principal component analysis and broad learning system

H Zhao, J Zheng, J Xu, W Deng - IEEE Access, 2019‏ - ieeexplore.ieee.org
Traditional feature extraction methods are used to extract the features of signal to construct
the fault feature matrix, which exists the complex structure, higher correlation, and …

Multilevel information fusion for induction motor fault diagnosis

J Wang, P Fu, L Zhang, RX Gao… - IEEE/ASME Transactions …, 2019‏ - ieeexplore.ieee.org
Condition monitoring and fault diagnosis are of significance to improve the safety and
reliability of motors, given their widespread applications in virtually every branch of the …

An optimized adaptive PReLU-DBN for rolling element bearing fault diagnosis

G Niu, X Wang, M Golda, S Mastro, B Zhang - Neurocomputing, 2021‏ - Elsevier
Rolling element bearings are critical components in industrial rotating machines. Faults and
failures of bearings can cause degradation of machine performance or even a catastrophe …