On the public citation graph

Probabilistic bearing fault diagnosis using Gaussian process with tailored feature extraction

https://doi.org/10.1007/s00170-021-08392-6

0 signed · 75 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.

Claim with ORCID

Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/bimj.200390007openalex-snapshot

Ratio Estimators in Stratified Random Sampling

inferredcites →https://doi.org/10.1007/s00170-019-04333-6openalex-snapshot

Early fault diagnosis of rolling bearing based on noise-assisted signal feature enhancement and stochastic resonance for intelligent manufacturing

inferredcites →https://doi.org/10.1007/s00170-019-04729-4openalex-snapshot

Novel predictive features using a wrapper model for rolling bearing fault diagnosis based on vibration signal analysis

inferredcites →https://doi.org/10.1007/s00170-020-06401-8openalex-snapshot

Rolling bearing fault diagnosis based on feature fusion with parallel convolutional neural network

inferredcites →https://doi.org/10.1007/s00170-021-07253-6openalex-snapshot

Harnessing fuzzy neural network for gear fault diagnosis with limited data labels

inferredcites →https://doi.org/10.1007/s00521-016-2294-8openalex-snapshot

Deep learning in vision-based static hand gesture recognition

inferredcites →https://doi.org/10.1007/s00521-019-04097-wopenalex-snapshot

A transfer convolutional neural network for fault diagnosis based on ResNet-50

inferredcites →https://doi.org/10.1007/s10845-019-01511-xopenalex-snapshot

Support vector machines based non-contact fault diagnosis system for bearings

inferredcites →https://doi.org/10.1007/s10845-020-01579-wopenalex-snapshot

A case study of conditional deep convolutional generative adversarial networks in machine fault diagnosis

inferredcites →https://doi.org/10.1007/s521-001-8051-zopenalex-snapshot

Kernel PCA for Feature Extraction and De-Noising in Nonlinear Regression

inferredcites →https://doi.org/10.1016/j.asoc.2018.09.037openalex-snapshot

Roller bearing fault diagnosis using stacked denoising autoencoder in deep learning and Gath–Geva clustering algorithm without principal component analysis and data label

inferredcites →https://doi.org/10.1016/j.asoc.2019.105854openalex-snapshot

Stacked autoencoder based deep random vector functional link neural network for classification

inferredcites →https://doi.org/10.1016/j.compstruc.2015.05.003openalex-snapshot

A residual-based Gaussian process model framework for finite element model updating

inferredcites →https://doi.org/10.1016/j.engstruct.2014.06.028openalex-snapshot

Analytical uncertainty quantification for modal frequencies with structural parameter uncertainty using a Gaussian process metamodel

inferredcites →https://doi.org/10.1016/j.eswa.2021.115397openalex-snapshot

Application of small sample virtual expansion and spherical mapping model in wind turbine fault diagnosis

inferredcites →https://doi.org/10.1016/j.jsv.2017.09.034openalex-snapshot

Uncertainty quantification in structural dynamic analysis using two-level Gaussian processes and Bayesian inference

inferredcites →https://doi.org/10.1016/j.measurement.2011.11.018openalex-snapshot

A novel linear ridgelet network approach for analog fault diagnosis using wavelet-based fractal analysis and kernel PCA as preprocessors

inferredcites →https://doi.org/10.1016/j.measurement.2019.06.029openalex-snapshot

A sparse stacked denoising autoencoder with optimized transfer learning applied to the fault diagnosis of rolling bearings

inferredcites →https://doi.org/10.1016/j.measurement.2020.108371openalex-snapshot

Rolling bearing fault diagnosis using variational autoencoding generative adversarial networks with deep regret analysis

inferredcites →https://doi.org/10.1016/j.measurement.2021.109088openalex-snapshot

A new bearing fault diagnosis method based on signal-to-image mapping and convolutional neural network

inferredcites →https://doi.org/10.1016/j.measurement.2021.110023openalex-snapshot

A bearing fault diagnosis method based on multiscale dispersion entropy and GG clustering

inferredcites →https://doi.org/10.1016/j.neucom.2010.12.003openalex-snapshot

A novel approach for analog fault diagnosis based on neural networks and improved kernel PCA

inferredcites →https://doi.org/10.1016/j.neucom.2015.11.044openalex-snapshot

Novel segmented stacked autoencoder for effective dimensionality reduction and feature extraction in hyperspectral imaging

inferredcites →https://doi.org/10.1016/j.renene.2020.04.041openalex-snapshot

Mahalanobis semi-supervised mapping and beetle antennae search based support vector machine for wind turbine rolling bearings fault diagnosis

inferredcites →https://doi.org/10.1016/j.ymssp.2015.04.021openalex-snapshot

Rolling element bearing diagnostics using the Case Western Reserve University data: A benchmark study

inferredcites →https://doi.org/10.1016/j.ymssp.2017.06.022openalex-snapshot

A deep convolutional neural network with new training methods for bearing fault diagnosis under noisy environment and different working load

inferredcites →https://doi.org/10.1016/j.ymssp.2018.12.051openalex-snapshot

An intelligent fault diagnosis approach based on transfer learning from laboratory bearings to locomotive bearings

inferredcites →https://doi.org/10.1016/j.ymssp.2020.107121openalex-snapshot

Structural model updating using adaptive multi-response Gaussian process meta-modeling

inferredcites →https://doi.org/10.1016/j.ymssp.2021.108139openalex-snapshot

Data synthesis using deep feature enhanced generative adversarial networks for rolling bearing imbalanced fault diagnosis

inferredcites →https://doi.org/10.1017/s0890060401153011openalex-snapshot

A case study on multisensor data fusion for imbalance diagnosis of rotating machinery

inferredcites →https://doi.org/10.1088/0957-0233/26/11/115002openalex-snapshot

Rolling bearing fault diagnosis using an optimization deep belief network

inferredcites →https://doi.org/10.1088/1361-6501/abda97openalex-snapshot

Bearing fault diagnosis method based on similarity measure and ensemble learning

inferredcites →https://doi.org/10.1109/access.2017.2720965openalex-snapshot

Transfer Learning With Neural Networks for Bearing Fault Diagnosis in Changing Working Conditions

inferredcites →https://doi.org/10.1109/access.2017.2740968openalex-snapshot

Cleaning Method for Status Monitoring Data of Power Equipment Based on Stacked Denoising Autoencoders

inferredcites →https://doi.org/10.1109/access.2018.2837621openalex-snapshot

Preprocessing-Free Gear Fault Diagnosis Using Small Datasets With Deep Convolutional Neural Network-Based Transfer Learning

inferredcites →https://doi.org/10.1109/access.2020.3009644openalex-snapshot

A Deep Learning Based Fault Diagnosis Method With Hyperparameter Optimization by Using Parallel Computing

inferredcites →https://doi.org/10.1109/ecce.2018.8557651openalex-snapshot

Deep Neural Network Based Bearing Fault Diagnosis of Induction Motor Using Fast Fourier Transform Analysis

inferredcites →https://doi.org/10.1109/jsen.2020.3004515openalex-snapshot

Non-Invasive Vibration Measurement for Diagnosis of Bearing Faults in 3-Phase Squirrel Cage Induction Motor Using Microwave Sensor

inferredcites →https://doi.org/10.1109/lsp.2014.2324759openalex-snapshot

Autoencoder-based Unsupervised Domain Adaptation for Speech Emotion Recognition

inferredcites →https://doi.org/10.1109/vtc2020-spring48590.2020.9129461openalex-snapshot

Intrusion detection on robot cameras using spatio-temporal autoencoders: A self-driving car application

inferredcites →https://doi.org/10.1115/1.4035107openalex-snapshot

Design Optimization Toward Alleviating Forced Response Variation in Cyclically Periodic Structure Using Gaussian Process

inferredcites →https://doi.org/10.1115/1.4047700openalex-snapshot

Uncertainty Quantification of Mode Shape Variation Utilizing Multi-Level Multi-Response Gaussian Process

inferredcites →https://doi.org/10.1177/0954406219875756openalex-snapshot

Raw vibration signal pattern recognition with automatic hyper-parameter-optimized convolutional neural network for bearing fault diagnosis

inferredcites →https://doi.org/10.1177/1077546320911484openalex-snapshot

Intelligent fault diagnosis of rolling bearings using variational mode decomposition and self-organizing feature map

inferredcites →https://doi.org/10.3390/e21040409openalex-snapshot

A Review of Early Fault Diagnosis Approaches and Their Applications in Rotating Machinery

inferredcites →https://doi.org/10.3390/s16060895openalex-snapshot

Fault Diagnosis for Rotating Machinery Using Vibration Measurement Deep Statistical Feature Learning

inferredcites →https://doi.org/10.3390/s19051088openalex-snapshot

Bearing Fault Diagnosis Method Based on Deep Convolutional Neural Network and Random Forest Ensemble Learning

inferredcites →https://doi.org/10.7551/mitpress/10187.001.0001openalex-snapshot

Decision Making Under Uncertainty

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4683970openalex-extracted

Scalable and Reliable Deep Transfer Learning for Intelligent Fault Detection Via Multi-Scale Neural Processes Embedded with Knowledge

inferred← citeshttps://doi.org/10.2139/ssrn.4811425openalex-extracted

Scalable and Reliable Deep Transfer Learning for Intelligent Fault Detection Via Multi-Scale Neural Processes Embedded with Knowledge

inferred← citeshttps://doi.org/10.1007/s00170-022-10392-zopenalex-snapshot

Enhanced feature extraction for machinery condition monitoring using recurrence plot and quantification measure

inferred← citeshttps://doi.org/10.1007/s42417-025-01913-7openalex-snapshot

A Comprehensive Survey of Multi-View Intelligent Fault Diagnosis Tailored to the Sensor, Machinery Equipment, and Industrial System Faults

inferred← citeshttps://doi.org/10.1016/j.apm.2023.05.042openalex-snapshot

A wavelet neural network informed by time-domain signal preprocessing for bearing remaining useful life prediction

inferred← citeshttps://doi.org/10.1016/j.ifacol.2022.11.279openalex-snapshot

Probabilistic Gear Fault Diagnosis Using Bayesian Convolutional Neural Network

inferred← citeshttps://doi.org/10.1016/j.jmsy.2023.07.012openalex-snapshot

Towards trustworthy rotating machinery fault diagnosis via attention uncertainty in transformer

inferred← citeshttps://doi.org/10.1016/j.measurement.2025.119419openalex-snapshot

A multi-modal framework for intelligent bearing fault diagnosis of switched reluctance motor

inferred← citeshttps://doi.org/10.1016/j.neucom.2025.131364openalex-snapshot

Scalable and reliable deep transfer learning for intelligent fault detection via multi-scale neural processes embedded with prior knowledge

inferred← citeshttps://doi.org/10.1016/j.solener.2026.114524openalex-snapshot

An interpretable uncertainty quantification mechanism based photovoltaic array fault diagnosis and unknown fault incremental model

inferred← citeshttps://doi.org/10.1016/j.ymssp.2025.112588openalex-snapshot

Dynamic model-assisted disentanglement framework for rolling bearing fault diagnosis under time-varying speed conditions

inferred← citeshttps://doi.org/10.1080/10589759.2025.2569783openalex-snapshot

DGT-former: a dual-channel time-frequency fusion model for remaining useful life prediction of rolling bearings

inferred← citeshttps://doi.org/10.1088/1361-6501/ad1673openalex-snapshot

A fault diagnosis method based on feature-level fusion of multi-sensor information for rotating machinery

inferred← citeshttps://doi.org/10.1088/1361-6501/ae0063openalex-snapshot

Enhanced brazing defect detection in automotive air conditioning heat exchangers using a novel deep learning transformer model

inferred← citeshttps://doi.org/10.1088/2631-8695/adfa69openalex-snapshot

Process fault classification based on label propagation and fault relevant ladder network

inferred← citeshttps://doi.org/10.1109/access.2024.3455355openalex-snapshot

Weak Feature Extraction Method for Bearing Faults Under Low-Speed Heavy-Duty Conditions

inferred← citeshttps://doi.org/10.1109/icdsns58469.2023.10244972openalex-snapshot

Bearing Fault Diagnosis With Envelope Analysis and Machine Learning Approaches Using CWRU Dataset

inferred← citeshttps://doi.org/10.1109/icmnwc63764.2024.10872274openalex-snapshot

Class Contribution Feature Weighting Based K-Nearest Neighbor for Fault Detection and Diagnosis in Vibration Signal Processing

inferred← citeshttps://doi.org/10.1109/tii.2023.3241587openalex-snapshot

Trustworthy Fault Diagnosis With Uncertainty Estimation Through Evidential Convolutional Neural Networks

inferred← citeshttps://doi.org/10.1115/1.4065777openalex-snapshot

An Enhanced Modeling Framework for Bearing Fault Simulation and Machine Learning-Based Identification With Bayesian-Optimized Hyperparameter Tuning

inferred← citeshttps://doi.org/10.1177/10775463221091601openalex-snapshot

A hierarchical deep learning framework for combined rolling bearing fault localization and identification with data fusion

inferred← citeshttps://doi.org/10.1177/10775463231211403openalex-snapshot

Joint loss learning-enabled semi-supervised autoencoder for bearing fault diagnosis under limited labeled vibration signals

inferred← citeshttps://doi.org/10.3390/electronics13153081openalex-snapshot

EffiMultiOrthoBearNet: An Efficient Lightweight Architecture for Bearing Fault Diagnosis

inferred← citeshttps://doi.org/10.3390/s23083860openalex-snapshot

Stochastic Resonance with Parameter Estimation for Enhancing Unknown Compound Fault Detection of Bearings

inferred← citeshttps://doi.org/10.3390/s23239437openalex-snapshot

A Multiplier-Free Convolution Neural Network Hardware Accelerator for Real-Time Bearing Condition Detection of CNC Machinery

inferred← citeshttps://doi.org/10.3934/era.2023359openalex-snapshot

Adaptive clustering algorithm based on improved marine predation algorithm and its application in bearing fault diagnosis

inferred← citeshttps://doi.org/10.3934/era.2024012openalex-snapshot

Research on filtering method of rolling bearing vibration signal based on improved Morlet wavelet

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.