Papers Fault Detection
“Fault Detection” 태그가 달린 논문 511편 · 필터 해제
Smart fault detection in satellite electrical power system
This paper presents an new approach for detecting in the electrical power system of satellites operating in Low Earth Orbit (LEO) without an Attitude Determination and Control Subsystem (ADCS). Components of these system…
DiagnosticFault DetectionPredictive Maintenance Optimization for Smart Vending Machines Using IoT and Machine Learning
The increasing proliferation of vending machines in public and commercial environments has placed a growing emphasis on operational efficiency and customer satisfaction. Traditional maintenance approaches either reactive…
Fault DetectionSchedulingRecursive-ARX for Grid-Edge Fault Detection
Future electrical grids will require new ways to identify faults as inverters are not capable of supplying large fault currents to support existing fault detection methods and because distributed resources may feed fault…
Fault DetectionObserver Switching Strategy for Enhanced State Estimation in CSTR Networks
Accurate state estimation is essential for monitoring and controlling nonlinear chemical reactors, such as continuous stirred-tank reactors (CSTRs), where limited sensor coverage and process uncertainties hinder real-tim…
Fault DetectionState EstimationBattBee: Equivalent Circuit Modeling and Early Detection of Thermal Runaway Triggered by Internal Short Circuits for Lithium-Ion Batteries
Lithium-ion batteries are the enabling power source for transportation electrification. However, in real-world applications, they remain vulnerable to internal short circuits (ISCs) and the consequential risk of thermal …
Fault DetectionTemporal cross-validation impacts multivariate time series subsequence anomaly detection evaluation
Evaluating anomaly detection in multivariate time series (MTS) requires careful consideration of temporal dependencies, particularly when detecting subsequence anomalies common in fault detection scenarios. While time se…
Anomaly DetectionBenchmarkingFault DetectionTime SeriesJoint System Modeling Approach for Fault Simulation of Start-er/Generator and Gas Generator in All-Electric APU
This paper presents a joint system modeling approach for fault simulation of all-electric auxiliary power unit (APU), integrating starter/generator turn-to-turn short circuit (TTSC) faults with gas generator gas-path fau…
AllComputational EfficiencyFault DetectionInterturn Fault Detection in IPMSMs: Two Adaptive Observer-based Solutions
In this paper we address the problem of online detection of inter-turn short-circuit faults (ITSCFs) that occur in permanent magnet synchronous motors (PMSMs). We propose two solutions to this problem: (i) a very simple …
Fault Detectionparameter estimationTime-Series Learning for Proactive Fault Prediction in Distributed Systems with Deep Neural Structures
This paper addresses the challenges of fault prediction and delayed response in distributed systems by proposing an intelligent prediction method based on temporal feature learning. The method takes multi-dimensional per…
Fault DetectionPredictionTime SeriesSelection Mechanisms for Sequence Modeling using Linear State Space Models
Recent advancements in language modeling tasks have been driven by architectures such as Transformers and, more recently, by Selective State Space Models (SSMs). In this paper, we introduce an alternative selection mecha…
Fault DetectionLanguage ModelingLanguage ModellingMamba+1Impact of Data Sparsity on Machine Learning for Fault Detection in Power System Protection
Germany's transition to a renewable energy-based power system is reshaping grid operations, requiring advanced monitoring and control to manage decentralized generation. Machine learning (ML) has emerged as a powerful to…
Fault DetectionEvoGPT: Enhancing Test Suite Robustness via LLM-Based Generation and Genetic Optimization
Large Language Models (LLMs) have recently emerged as promising tools for automated unit test generation. We introduce a hybrid framework called EvoGPT that integrates LLM-based test generation with evolutionary search t…
DiversityFault Detectionsoftware testingCloud-Based AI Systems: Leveraging Large Language Models for Intelligent Fault Detection and Autonomous Self-Healing
With the rapid development of cloud computing systems and the increasing complexity of their infrastructure, intelligent mechanisms to detect and mitigate failures in real time are becoming increasingly important. Tradit…
Anomaly DetectionCloud ComputingFault DetectionNatural Language UnderstandingOnline Isolation Forest
The anomaly detection literature is abundant with offline methods, which require repeated access to data in memory, and impose impractical assumptions when applied to a streaming context. Existing online anomaly detectio…
Anomaly DetectionFault DetectionNeural Associative Skill Memories for safer robotics and modelling human sensorimotor repertoires
Modern robots face challenges shared by humans, where machines must learn multiple sensorimotor skills and express them adaptively. Equipping robots with a human-like memory of how it feels to do multiple stereotypical m…
Fault DetectionImplicit Neural Representation of Waveform Measurements in Power Systems Waveform Data Analysis
There is currently a paradigm shift in several power system monitoring applications, such as incipient fault detection and monitoring inverter-based resources, to transition from traditional phasor analytics to more info…
Fault DetectionFault Detection Method for Power Conversion Circuits Using Thermal Image and Convolutional Autoencoder
A fault detection method for power conversion circuits using thermal images and a convolutional autoencoder is presented. The autoencoder is trained on thermal images captured from a commercial power module at randomly v…
Anomaly DetectionFault DetectionImage AugmentationEfficient Fault Detection in WSN Based on PCA-Optimized Deep Neural Network Slicing Trained with GOA
Fault detection in Wireless Sensor Networks (WSNs) is crucial for reliable data transmission and network longevity. Traditional fault detection methods often struggle with optimizing deep neural networks (DNNs) for effic…
Fault DetectionFault Diagnosis of 3D-Printed Scaled Wind Turbine Blades
This study presents an integrated methodology for fault detection in wind turbine blades using 3D-printed scaled models, finite element simulations, experimental modal analysis, and machine learning techniques. A scaled …
Fault DetectionFault DiagnosisStructural Health MonitoringEfficient Fairness Testing in Large Language Models: Prioritizing Metamorphic Relations for Bias Detection
Large Language Models (LLMs) are increasingly deployed in various applications, raising critical concerns about fairness and potential biases in their outputs. This paper explores the prioritization of metamorphic relati…
Bias DetectionDiversityFairnessFault Detection+1