Fault Diagnosis
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Benchmarks
Most implemented
ToyADMOS2: Another dataset of miniature-machine operating sounds for anomalous sound detection under domain shift conditions
Bearing Fault Diagnosis Base on Multi-scale CNN and LSTM Model
Demystifying and Extracting Fault-indicating Information from Logs for Failure Diagnosis
BearLLM: A Prior Knowledge-Enhanced Bearing Health Management Framework with Unified Vibration Signal Representation
Lighter, Better, Faster Multi-Source Domain Adaptation with Gaussian Mixture Models and Optimal Transport
GPLA-12: An Acoustic Signal Dataset of Gas Pipeline Leakage
Papers
Deep Learning-Based Detection of Electrical Faults and Power Quality Disturbances in Aerospace Power Systems
More Electric Aircraft require fast and reliable monitoring of high-frequency electrical networks, yet most power quality disturbance and fault diagnosis methods are developed for conventional 50 or 60 Hz grids. This wor…
Fault DiagnosisA Kernel-Based Modular Discriminant Analysis Framework for Small-Sample Learning
The small-sample-size (SSS) problem remains a fundamental challenge in machine learning when labeled data are scarce due to cost, accessibility, or ethical constraints. While numerous approaches have been proposed, exist…
Hyperspectral Image ClassificationMedical DiagnosisFace RecognitionFault DiagnosisRad-R: A Raw-ADC Radar Dataset and Capture-Invariant SSM for Hardware-Fault Diagnosis
Automotive mmWave radar can develop vibration, antenna misalignment, radome blockage, and receive-channel degradation that corrupt the signal before perception begins. Data for these faults are scarce because each condit…
Fault DiagnosisFaulT-Bench: Towards Benchmarking Network Troubleshooting LLM Agents under Unreliable User Tickets
LLM-based agents are increasingly proposed for network fault diagnosis, but existing benchmarks evaluate them only on accurate tickets and always assume a fault is present, conditions rarely met in practice. We present F…
Fault DiagnosisFree-Text Evaluation of LLMs for 5G Domain Knowledge and Fault Analysis using LLM-as-Judge
Real-world fault analysis in 5G and emerging 6G networks demands domain expertise to analyze free-text diagnostics, including root-cause explanations and recommended actions. LLMs have emerged as a promising approach to …
Fault DiagnosisText GenerationGraph Machine Learning: An Opportunity for Power Systems
Modern power systems face growing operational complexity driven by the integration of renewable energy sources, decentralization, and the need for real-time decision-making across a wide range of timescales. Addressing t…
Computational EfficiencyFault Diagnosis