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Fault Diagnosis

Papers

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Showing 201–225 of 375 papers

TitleStatusHype
A Composite Fault Diagnosis Model for NPPs Based on Bayesian-EfficientNet Module—0
A comprehensive review on convolutional neural network in machine fault diagnosis—0
A Comprehensive Survey of Belief Rule Base (BRB) Hybrid Expert system: Bridging Decision Science and Professional Services—0
A Cost-Sensitive Deep Belief Network for Imbalanced Classification—0
Acoustic Signal Analysis with Deep Neural Network for Detecting Fault Diagnosis in Industrial Machines—0
A crayfish-optimized wavelet filter and its application to fault diagnosis—0
Active Foundational Models for Fault Diagnosis of Electrical Motors—0
A data-driven approach to UIO-based fault diagnosis—0
Addressing Domain Shift via Knowledge Space Sharing for Generalized Zero-Shot Industrial Fault Diagnosis—0
Advancing machine fault diagnosis: A detailed examination of convolutional neural networks—0
Adversarial adaptive 1-D convolutional neural networks for bearing fault diagnosis under varying working condition—0
A fault detection scheme for PV panels in large scale PV stations with complex installation conditions—0
A Federated Distributionally Robust Support Vector Machine with Mixture of Wasserstein Balls Ambiguity Set for Distributed Fault Diagnosis—0
A Heterogeneous Graph-Based Multi-Task Learning for Fault Event Diagnosis in Smart Grid—0
AI-driven Transformer Model for Fault Prediction in Non-Linear Dynamic Automotive System—0
AI Explainability for Power Electronics: From a Lipschitz Continuity Perspective—0
AIOptimizer - Software performance optimisation prototype for cost minimisation—0
A lightweight network for photovoltaic cell defect detection in electroluminescence images based on neural architecture search and knowledge distillation—0
A Multimodal Lightweight Approach to Fault Diagnosis of Induction Motors in High-Dimensional Dataset—0
A Multi-size Kernel based Adaptive Convolutional Neural Network for Bearing Fault Diagnosis—0
A multi-stage semi-supervised improved deep embedded clustering method for bearing fault diagnosis under the situation of insufficient labeled samples—0
A Multi-State Diagnosis and Prognosis Framework with Feature Learning for Tool Condition Monitoring—0
An Adaptive feature mode decomposition based on a novel health indicator for bearing fault diagnosis—0
An AI-Driven Approach to Wind Turbine Bearing Fault Diagnosis from Acoustic Signals—0
An alternative paradigm of fault diagnosis in dynamic systems: orthogonal projection-based methods—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DANNAccuray80.22—Unverified
2LSTMAccuray61.56—Unverified