Fault diagnosis and self-healing for smart manufacturing: a review

J Aldrini, I Chihi, L Sidhom - Journal of Intelligent Manufacturing, 2024 - Springer
Manufacturing systems are becoming more sophisticated and expensive, particularly with
the development of the intelligent industry. The complexity of the architecture and concept of …

Research progress on oil-immersed transformer mechanical condition identification based on vibration signals

YT Sun, HZ Ma - Renewable and Sustainable Energy Reviews, 2024 - Elsevier
In recent years, vibration signals have been widely applied for the identification of
mechanical states in oil-immersed transformers. This paper, following the framework of …

An expert system for rotating machine fault detection using vibration signal analysis

A Kafeel, S Aziz, M Awais, MA Khan, K Afaq, SA Idris… - Sensors, 2021 - mdpi.com
Accurate and early detection of machine faults is an important step in the preventive
maintenance of industrial enterprises. It is essential to avoid unexpected downtime as well …

Computational intelligence for preventive maintenance of power transformers

SY Wong, X Ye, F Guo, HH Goh - Applied Soft Computing, 2022 - Elsevier
Power transformers are an indispensable equipment in power transmission and distribution
systems, and failures or hidden defects in power transformers can cause operational and …

System for tool-wear condition monitoring in cnc machines under variations of cutting parameter based on fusion stray flux-current processing

AY Jaen-Cuellar, RA Osornio-Ríos, M Trejo-Hernández… - Sensors, 2021 - mdpi.com
The computer numerical control (CNC) machine has recently taken a fundamental role in the
manufacturing industry, which is essential for the economic development of many countries …

[HTML][HTML] Gradual wear diagnosis of outer-race rolling bearing faults through artificial intelligence methods and stray flux signals

I Zamudio-Ramirez, RA Osornio-Rios… - Electronics, 2021 - mdpi.com
Electric motors have been widely used as fundamental elements for driving kinematic chains
on mechatronic systems, which are very important components for the proper operation of …

Convolutional neural network-based transformer fault diagnosis using vibration signals

C Li, J Chen, C Yang, J Yang, Z Liu, P Davari - Sensors, 2023 - mdpi.com
Fast and accurate fault diagnosis is crucial to transformer safety and cost-effectiveness.
Recently, vibration analysis for transformer fault diagnosis is attracting increasing attention …

[HTML][HTML] Research on a Transformer Vibration Fault Diagnosis Method Based on Time-Shift Multiscale Increment Entropy and CatBoost

H Shang, T Huang, Z Wang, J Li, S Zhang - Entropy, 2024 - mdpi.com
A mechanical vibration fault diagnosis is a key means of ensuring the safe and stable
operation of transformers. To achieve an accurate diagnosis of transformer vibration faults …

[HTML][HTML] Analysis of vibration signals based on machine learning for crack detection in a low-power wind turbine

AH Rangel-Rodriguez, D Granados-Lieberman… - Entropy, 2023 - mdpi.com
Currently, renewable energies, including wind energy, have been experiencing significant
growth. Wind energy is transformed into electric energy through the use of wind turbines …

Application of fractional-order integral transforms in the diagnosis of electrical system conditions

HM Cortés Campos, JF Gomez-Aguilar… - Fractals, 2024 - World Scientific
This paper proposes a methodology for the diagnosis of electrical system conditions using
fractional-order integral transforms for feature extraction. This work proposes three feature …