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Fault Diagnosis of Delta 3D Printers Using Transfer Support Vector Machine With Attitude Signals

https://doi.org/10.1109/access.2019.2905264

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What this work says

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

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Gearbox Fault Diagnosis Based on Mel-Frequency Cepstral Coefficients and Support Vector Machine

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Experimental validation of an actuator fault tolerant control system using virtual sensor: Application in a double pipe heat exchanger

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Dynamic condition monitoring for 3D printers by using error fusion of multiple sparse auto-encoders

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Deep transfer network with joint distribution adaptation: A new intelligent fault diagnosis framework for industry application

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A novel Switching Unscented Kalman Filter method for remaining useful life prediction of rolling bearing

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Research on power coefficient of wind turbines based on SCADA data

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Condition monitoring of gearboxes using synchronously averaged electric motor signals

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Gearbox fault diagnosis based on deep random forest fusion of acoustic and vibratory signals

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Extracting repetitive transients for rotating machinery diagnosis using multiscale clustered grey infogram

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Nonlinear sensor fault diagnosis using mixture of probabilistic PCA models

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HVSRMS localization formula and localization law: Localization diagnosis of a ball bearing outer ring fault

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Integrating structured biological data by Kernel Maximum Mean Discrepancy

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Deep Decoupling Convolutional Neural Network for Intelligent Compound Fault Diagnosis

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Transfer Joint Matching for Unsupervised Domain Adaptation

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Domain adaptation for object recognition: An unsupervised approach

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Transfer Feature Learning with Joint Distribution Adaptation

inferredcites →https://doi.org/10.1109/icdm.2017.150openalex-snapshot

Balanced Distribution Adaptation for Transfer Learning

inferredcites →https://doi.org/10.1109/icphm.2016.7542845openalex-snapshot

On cross-domain feature fusion in gearbox fault diagnosis under various operating conditions based on Transfer Component Analysis

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Bearing fault diagnosis based on SVD feature extraction and transfer learning classification

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A Systematic Review of Fuzzy Formalisms for Bearing Fault Diagnosis

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A Survey on Transfer Learning

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Adaptation Regularization: A General Framework for Transfer Learning

inferredcites →https://doi.org/10.1109/tnn.2010.2091281openalex-snapshot

Domain Adaptation via Transfer Component Analysis

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Domain Transfer Multiple Kernel Learning

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A New Deep Transfer Learning Based on Sparse Auto-Encoder for Fault Diagnosis

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Visual Domain Adaptation with Manifold Embedded Distribution Alignment

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Return of Frustratingly Easy Domain Adaptation

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Domain adaptation with structural correspondence learning

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A comparison of fuzzy clustering algorithms for bearing fault diagnosis

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

inferredcites →https://doi.org/10.3901/jme.2013.01.081openalex-snapshot

Variable Nearest Neighbor Locally Linear Embedding and Applications in Bearing Condition Recognition

What points at this work

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

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Incorporation of machine learning in additive manufacturing: a review

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Knowledge transfer in fault diagnosis of rotary machines

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Data-Driven Fault Detection for Dynamic Systems With Performance Degradation: A Unified Transfer Learning Framework

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Transfer Learning-Motivated Intelligent Fault Diagnosis Designs: A Survey, Insights, and Perspectives

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Applications of Supervised Machine Learning Algorithms in Additive Manufacturing: A Review

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Experimental Research on On-line Monitoring and Compensation Algorithm of 3D Printing Based on Machine Vision

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Generative Transfer Learning for Intelligent Fault Diagnosis of the Wind Turbine Gearbox

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Exploring Machine Learning-Based Fault Monitoring for Polymer-Based Additive Manufacturing: Challenges and Opportunities

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Fault Diagnosis in a Four-Arm Delta Robot Based on Wavelet Scattering Networks and Artificial Intelligence Techniques

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Multiscale study of the intelligent optimization of dimensional stability and mechanical properties of structures obtained by additive manufacturing

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