A comprehensive survey on support vector machine classification: Applications, challenges and trends

J Cervantes, F Garcia-Lamont, L Rodríguez-Mazahua… - Neurocomputing, 2020 - Elsevier
In recent years, an enormous amount of research has been carried out on support vector
machines (SVMs) and their application in several fields of science. SVMs are one of the …

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 …

Modeling the SOFC by BP neural network algorithm

S Song, X Xiong, X Wu, Z Xue - International Journal of Hydrogen Energy, 2021 - Elsevier
Solid oxide fuel cells (SOFCs) are complex systems in which electrochemistry,
thermophysics and ion conduction occur simultaneously. The coupling of the multi-physics …

Review of machine learning based fault detection for centrifugal pump induction motors

CE Sunal, V Dyo, V Velisavljevic - IEEE access, 2022 - ieeexplore.ieee.org
Centrifugal pumps are an integral part of many industrial processes and are used
extensively in water supply, sewage, heating and cooling systems. While there are several …

Performance evaluation of LSTM and Bi-LSTM using non-convolutional features for blockage detection in centrifugal pump

NS Ranawat, J Prakash, A Miglani… - Engineering Applications of …, 2023 - Elsevier
Blockages in the suction or discharge side of the pump adversely affect the pump's
performance by reducing the flow rate and head, increasing vibration, noise, and …

Multi-scale and multi-layer perceptron hybrid method for bearings fault diagnosis

S Xie, Y Li, H Tan, R Liu, F Zhang - International Journal of Mechanical …, 2022 - Elsevier
The progressive growth in demand and requirements for bearing problem diagnostics in the
operating segment of trains has resulted from an increase in train speed and the …

A novel deep autoencoder and hyperparametric adaptive learning for imbalance intelligent fault diagnosis of rotating machinery

W Li, Z Shang, M Gao, S Qian, B Zhang… - … Applications of Artificial …, 2021 - Elsevier
Relying on the purpose of transmitting force and torque, rotating machinery is widely used in
various industrial equipment. The failure of rotating machinery leads to large maintenance …

Research on fault diagnosis technology of centrifugal pump blade crack based on PCA and GMM

S Cao, Z Hu, X Luo, H Wang - Measurement, 2021 - Elsevier
Centrifugal pumps are widely used in modern industry, and blades are the key parts of it.
The cracks on blades may result in a very serious consequence. In this paper, a fault …

Investigation of pressure pulsation induced by quasi-steady cavitation in a centrifugal pump

J Lu, J Liu, L Qian, X Liu, S Yuan, B Zhu, Y Dai - Physics of Fluids, 2023 - pubs.aip.org
To study the pressure pulsations induced by quasi-steady cavitation in a centrifugal pump,
the pressure pulsations at the pump inlet and outlet were experimentally investigated with …

A fault diagnosis framework for centrifugal pumps by scalogram-based imaging and deep learning

MJ Hasan, A Rai, Z Ahmad, JM Kim - IEEE Access, 2021 - ieeexplore.ieee.org
Centrifugal pumps are the most vital part of any process industry. A fault in centrifugal pump
can affect imperative industrial processes. To ensure reliable operation of the centrifugal …