Artificial Intelligence-Driven Prognostics and Health Management for Centrifugal Pumps: A Comprehensive Review
This comprehensive review explores data-driven methodologies that facilitate the prognostics and health management (PHM) of centrifugal pumps (CPs) while utilizing both vibration and non-vibration sensor data. This review investigates common fault types in CPs, while placing a specific emphasis on a...
Saved in:
| Main Authors: | Salman Khalid, Soo-Ho Jo, Syed Yaseen Shah, Joon Ha Jung, Heung Soo Kim |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
|
| Series: | Actuators |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-0825/13/12/514 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Optimal Design of a Liquid Hydrogen Centrifugal Pump Impeller
by: Catur Harsito, et al.
Published: (2024-12-01) -
Hybrid Deep Learning Model for Fault Diagnosis in Centrifugal Pumps: A Comparative Study of VGG16, ResNet50, and Wavelet Coherence Analysis
by: Wasim Zaman, et al.
Published: (2024-12-01) -
An Introduction to Sizing Centrifugal Pumps in Aquaculture
by: Jordan Neff, et al.
Published: (2022-11-01) -
Vibration Analysis of a Centrifugal Pump with Healthy and Defective Impellers and Fault Detection Using Multi-Layer Perceptron
by: Masoud Hatami Garousi, et al.
Published: (2024-10-01) -
Research Progress on Influence of Centrifugal Blood Pump on Blood Injury
by: Chenghong YE, et al.
Published: (2024-03-01)