Predictive monitoring of incipient faults in rotating machinery: a systematic review from data acquisition to artificial intelligence

K Saini, SS Dhami, Vanraj - Archives of Computational Methods in …, 2022 - Springer
Predictive maintenance is one of the major tasks in today's modern industries. All rotating
machines consisting of rotating elements such as gears, bearings etc are considered as the …

Non-invasive inspections: A review on methods and tools

M Alotaibi, B Honarvar Shakibaei Asli, M Khan - Sensors, 2021 - mdpi.com
Non-Invasive Inspection (NII) has become a fundamental tool in modern industrial
maintenance strategies. Remote and online inspection features keep operators fully aware …

Percussion-based bolt looseness monitoring using intrinsic multiscale entropy analysis and BP neural network

R Yuan, Y Lv, Q Kong, G Song - Smart Materials and Structures, 2019 - iopscience.iop.org
In this paper, a novel percussion-based bolt looseness monitoring approach using intrinsic
multiscale entropy analysis and back propagation (BP) neural network is proposed. The …

Performance degradation assessment of a wind turbine gearbox based on multi-sensor data fusion

Y Pan, R Hong, J Chen, J Singh, X Jia - Mechanism and machine theory, 2019 - Elsevier
Gearbox is a critical transmission component in the drivetrain of wind turbine having a
dominant failure rate and a highest downtime loss among all wind turbine subsystems …

Research of planetary gear fault diagnosis based on permutation entropy of CEEMDAN and ANFIS

M Kuai, G Cheng, Y Pang, Y Li - Sensors, 2018 - mdpi.com
For planetary gear has the characteristics of small volume, light weight and large
transmission ratio, it is widely used in high speed and high power mechanical system. Poor …

A Study of Fault Signal Noise Reduction Based on Improved CEEMDAN-SVD

S Zhao, L Ma, L Xu, M Liu, X Chen - Applied Sciences, 2023 - mdpi.com
In light of the challenges posed by the complex structural characteristics and significant
coupling of vibration signals in rotating machinery, this study proposes an adaptive noise …

CEEMDAN‐Based Permutation Entropy: A Suitable Feature for the Fault Identification of Spiral‐Bevel Gears

L Jiang, H Tan, X Li, L Chen, D Yang - Shock and Vibration, 2019 - Wiley Online Library
A spiral‐bevel gear is a basic transmission component and is widely used in mechanical
equipment; thus, it is important to monitor and diagnose its running state to ensure safe …

Composite multi-scale basic scale Entropy based on CEEMDAN and its application in hydraulic pump fault diagnosis

X Liu, X Yang, F Shao, W Liu, F Zhou, C Hu - IEEE Access, 2021 - ieeexplore.ieee.org
The hydraulic pump plays a very important role in the safe and stable operation of the
hydraulic system. Once it fails, it will cause immeasurable losses to the entire hydraulic …

[HTML][HTML] Artificial intelligence-based forecasting models for integrated energy system management planning: An exploration of the prospects for South Africa

S Krishnamurthy, OB Adewuyi, E Luwaca… - Energy Conversion and …, 2024 - Elsevier
The regional energy demand for Southern Africa has been predicted to increase by ten to
fourteen times between the years 2010 and 2070. Thus, to address the proliferation of …

MODWT and VMD based intelligent gearbox early stage fault detection approach

Mansi, K Saini, Vanraj, SS Dhami - Journal of Failure Analysis and …, 2021 - Springer
Gearbox, a crucial constituent of any plant machinery, always requires special attention as it
has to perform under considerable environmental conditions throughout its service life …