RTSMFFDE-HKRR: a fault diagnosis method for train bearing in noise environment

D He, Z Zhang, Z Jin, F Zhang, C Yi, S Liao - Measurement, 2025 - Elsevier
The bearings have been exposed to a noisy environment for an extended period, making it
challenging to identify fault characteristics accurately and resulting in low accuracy. In this …

[HTML][HTML] Vibration Signal Analysis for Intelligent Rotating Machinery Diagnosis and Prognosis: A Comprehensive Systematic Literature Review

I Bagri, K Tahiry, A Hraiba, A Touil, A Mousrij - Vibration, 2024 - mdpi.com
Many industrial processes, from manufacturing to food processing, incorporate rotating
elements as principal components in their production chain. Failure of these components …

Systematic Review on Fault Diagnosis on Rolling-Element Bearing

M Pandiyan, TN Babu - Journal of Vibration Engineering & Technologies, 2024 - Springer
Purpose To maintain machinery operations smoothly, Rolling-Element Bearings (REBs) are
utilized so that the entire equipment's safety is ensured. Sometimes, the safety of the …

Few-shot bearing fault diagnosis by semi-supervised meta-learning with graph convolutional neural network under variable working conditions

Z Liu, Z Peng - Measurement, 2025 - Elsevier
Aiming at the problems of low accuracy and weak generalization ability in fault diagnosis
caused by complex working conditions and limited fault samples of bearings, a few-shot …

Multi-feature spaces cross adaption transfer learning-based bearings piece-wise remaining useful life prediction under unseen degradation data

ZJ Li, DJ Cheng, HB Zhang, KL Zhou… - Advanced Engineering …, 2024 - Elsevier
In actual industry, rolling bearings always exhibit complex and uncertain degradation
processes, and it is difficult to collect sufficient full lifecycle data, resulting in the remaining …

Antenna for automated classification of mouth/neck activities using convolutional neural networks and smoothed time–frequency representations

S Ghosh, B Basu, A Nandi, M Das - Measurement, 2025 - Elsevier
Recognizing complicated motions of the mouth and neck, including eating, coughing,
breathing, etc, is vital for health monitoring and disease diagnosis. This study provides two …

PCA-IEM-DARNN: An enhanced dual-stage deep learning prediction model for concrete dam deformation based on feature decomposition

X Kang, Y Li, Y Zhang, L Wen, X Sun, J Wang - Measurement, 2025 - Elsevier
Deformation is a crucial indicator of structural integrity, essential for ensuring the long-term
safety of dams. Existing models face challenges in accurately simulating the strong …

New health indicators for the monitoring of bearing failures under variable loads

A Lourari, A Soualhi, K Medjaher… - Structural Health …, 2024 - journals.sagepub.com
Bearings are one of the most critical components in rotating machines. Unexpected failure of
this components may cause serious damages and unplanned breakdowns. In this paper, a …

A small sample rolling bearing fault diagnosis based on PSD-VME and DS evidence theory enhanced mRVM

Z Feng, Z Zhang - Computers and Electrical Engineering, 2024 - Elsevier
When small sample rolling bearing fault signals are interfered by signals with low
correlation, conducting effective fault diagnosis becomes challenging. To address this issue …

Enhanced fault feature extraction and bearing fault diagnosis using shearlet transform and deep learning

PD Swami, RK Jha, A Jat - Signal, Image and Video Processing, 2024 - Springer
Accurate bearing fault diagnosis is essential for ensuring the health and longevity of
mechanical systems. Traditional methods often struggle with the dynamic operating …