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A New Deep Stacked Architecture for Multi-Fault Machinery Identification With Imbalanced Samples

https://doi.org/10.1109/access.2021.3071796
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What this work says

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

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Geometric Design of Linkages
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An Approach to Fault Diagnosis Using Fuzzy Clustering Techniques
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Geometric Design of Linkages
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Combining multiple deep learning algorithms for prognostic and health management of aircraft
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Faulted gear identification of a rotating machinery based on wavelet transform and artificial neural network
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Applications of fault diagnosis in rotating machinery by using time series analysis with neural network
inferredcites →https://doi.org/10.1016/j.eswa.2010.09.072openalex-snapshot
Effect of number of features on classification of roller bearing faults using SVM and PSVM
inferredcites →https://doi.org/10.1016/j.jneumeth.2020.108885openalex-snapshot
Data augmentation for deep-learning-based electroencephalography
inferredcites →https://doi.org/10.1016/j.knosys.2019.105313openalex-snapshot
Deep transfer multi-wavelet auto-encoder for intelligent fault diagnosis of gearbox with few target training samples
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Classification of fault location and performance degradation of a roller bearing
inferredcites →https://doi.org/10.1016/j.measurement.2014.10.026openalex-snapshot
Diagnostics of gear deterioration using EEMD approach and PCA process
inferredcites →https://doi.org/10.1016/j.measurement.2019.01.063openalex-snapshot
Fault diagnosis of rolling bearing under fluctuating speed and variable load based on TCO Spectrum and Stacking Auto-encoder
inferredcites →https://doi.org/10.1016/j.measurement.2019.02.022openalex-snapshot
Rotor fault diagnosis using a convolutional neural network with symmetrized dot pattern images
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Artificial neural network-based modelling and fault detection of partial shaded photovoltaic modules
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Deep Decoupling Convolutional Neural Network for Intelligent Compound Fault Diagnosis
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Cross-Domain Fault Diagnosis of Rolling Element Bearings Using Deep Generative Neural Networks
inferredcites →https://doi.org/10.1109/tim.2017.2698738openalex-snapshot
Stacked Multilevel-Denoising Autoencoders: A New Representation Learning Approach for Wind Turbine Gearbox Fault Diagnosis
inferredcites →https://doi.org/10.1109/tim.2020.3043959openalex-snapshot
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Modified Stacked Autoencoder Using Adaptive Morlet Wavelet for Intelligent Fault Diagnosis of Rotating Machinery
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Some Experiments on Oil Whirl and Oil Whip
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Gear Defect Modeling of a Multiple‐Stage Gear Train
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Sliding Window Based Machine Learning System for the Left Ventricle Localization in MR Cardiac Images
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Reliable Fault Diagnosis of Rotary Machine Bearings Using a Stacked Sparse Autoencoder‐Based Deep Neural Network
inferredcites →https://doi.org/10.1155/2018/5105709openalex-snapshot
A Stacked Autoencoder-Based Deep Neural Network for Achieving Gearbox Fault Diagnosis
inferredcites →https://doi.org/10.1155/2018/7460419openalex-snapshot
Vibration‐Based Fault Diagnosis of Commutator Motor
inferredcites →https://doi.org/10.1177/0954406218805510openalex-snapshot
Multi-fault diagnosis of rolling bearing using fuzzy entropy of empirical mode decomposition, principal component analysis, and SOM neural network
inferredcites →https://doi.org/10.1177/1687814018811036openalex-snapshot
Gear fault diagnosis method based on wavelet-packet independent component analysis and support vector machine with kernel function fusion
inferredcites →https://doi.org/10.1784/insi.2014.56.11.622openalex-snapshot
Detection of machine soft foot with vibration analysis
inferredcites →https://doi.org/10.3390/app8122357openalex-snapshot
Bearing Fault Diagnosis under Variable Rotational Speeds Using Stockwell Transform-Based Vibration Imaging and Transfer Learning
inferredcites →https://doi.org/10.3390/s150923903openalex-snapshot
Multi-Stage Feature Selection by Using Genetic Algorithms for Fault Diagnosis in Gearboxes Based on Vibration Signal
inferredcites →https://doi.org/10.3390/s17030549openalex-snapshot
Fault Diagnosis from Raw Sensor Data Using Deep Neural Networks Considering Temporal Coherence
inferredcites →https://doi.org/10.3390/s17071564openalex-snapshot
Unsupervised Fault Diagnosis of a Gear Transmission Chain Using a Deep Belief Network
inferredcites →https://doi.org/10.3390/s18103510openalex-snapshot
Research on Fault Diagnosis of Gearbox with Improved Variational Mode Decomposition
inferredcites →https://doi.org/10.3390/s18113804openalex-snapshot
Application of Improved Singular Spectrum Decomposition Method for Composite Fault Diagnosis of Gear Boxes
inferredcites →https://doi.org/10.3390/s18113857openalex-snapshot
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inferredcites →https://doi.org/10.4028/www.scientific.net/kem.413-414.599openalex-snapshot
Experimental Investigation of Pedestal Looseness in a Rotor-Bearing System
inferredcites →https://doi.org/10.48550/arxiv.1609.08976openalex-snapshot
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inferredcites →https://doi.org/10.48550/arxiv.1711.04340openalex-snapshot
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Detection of Unbalance in Rotating Machines Using Shaft Deflection Measurement during Its Operation

What points at this work

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

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Applications of Artificial Intelligence for Fault Diagnosis of Rotating Machines: A Review
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A scoping review on multi-fault diagnosis of industrial rotating machines using multi-sensor data fusion
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A Robust Condition Monitoring Approach in Industrial Plants Based on the Pythagorean Membership Grades
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Imbalanced domain generalization via Semantic-Discriminative augmentation for intelligent fault diagnosis
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A federated cross-machine diagnostic framework for machine-level motors with extreme label shortage
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Fault sample generation under continuous degradation using CRGAN-MDTR: A conditional recurrent GAN with maximum degenerate trend retention
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A generalized method for diagnosing multi-faults in rotating machines using imbalance datasets of different sensor modalities
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Imbalance fault diagnosis under long-tailed distribution: Challenges, solutions and prospects
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A new generative adversarial network based imbalanced fault diagnosis method
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Multiaxis Accelerometer-Based Evaluation and Classification of Misalignment, Soft Foot, and Looseness Faults in Induction Motors
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A Systematic Review on Imbalanced Learning Methods in Intelligent Fault Diagnosis
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An Investigation Into the Behavior of Intelligent Fault Diagnostic Models Under Imbalanced Data
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Innovative Data Augmentation Using Lightweight Diffusion Transformer for Imbalanced Fault Diagnosis
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Innovative Data Augmentation Using Lightweight Diffusion Transformer for Imbalanced Fault Diagnosis
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Generative Artificial Intelligence for Chatter-Free Machining: A Critical Review on Synthetic Data, Application Pathways, and Future Grand Challenges
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Data Augmentation: A Multi-Perspective Survey on Data, Methods, and Applications
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