Results 11 to 20 of about 35,187 (315)
Sensors, 2023 The further identification of fault types for single line-to-ground faults (SLGFs) in distribution networks is conducive to determining the cause of grounding faults and formulating targeted measures for hidden danger treatment and fault prevention.
Jiajun Liu +4 more
doaj +2 more sources
A Deep Autoencoder-Based Convolution Neural Network Framework for Bearing Fault Classification in Induction Motors. [PDF]
Sensors (Basel), 2021 Fault diagnosis and classification for machines are integral to condition monitoring in the industrial sector. However, in recent times, as sensor technology and artificial intelligence have developed, data-driven fault diagnosis and classification have ...
Toma RN, Piltan F, Kim JM.
europepmc +2 more sources
Fault diagnosis of induction motor based on decision trees and adaptive neuro-fuzzy inference [PDF]
, 2009 This paper presents a fault diagnosis method based on adaptive neuro-fuzzy inference system (ANFIS) in combination with decision trees. Classification and regression tree (CART) which is one of the decision tree methods is used as a feature selection ...
Yang, Bo-Suk +5 more
core +1 more source
Hydraulic Rock Drill Fault Classification Using X−Vectors
Mathematics, 2023 Hydraulic rock drills are widely used in drilling, mining, construction, and engineering applications. They typically operate in harsh environments with high humidity, large temperature differences, and vibration.
Huixuan Ling +4 more
doaj +1 more source
Power System Fault Classification and Prediction Based on a Three-Layer Data Mining Structure
IEEE Access, 2020 In traditional fault diagnosis methods in power systems, it is difficult to accurately classify and predict the types of faults. With the emergence of big data technology, the fault classification and prediction methods based on big data analysis and ...
Yunliang Wang +3 more
doaj +1 more source
Machines, 2023 The use of deep learning for fault diagnosis is already a common approach. However, integrating discriminative information of fault types and scales into deep learning models for rich multitask fault feature diagnosis still deserves attention.
Ruihao Xin +4 more
doaj +1 more source
Thermal Image Enhancement using Bi-dimensional Empirical Mode Decomposition in Combination with Relevance Vector Machine for Rotating Machinery Fault Diagnosis [PDF]
, 2009 In this study, a novel fault diagnosis system for rotating machinery using thermal imaging is proposed. This system consists of bi-dimensional empirical mode decomposition (BEMD) for image enhancement, a generalized discriminant analysis (GDA) for ...
Yang, Bo-Suk +7 more
core +1 more source
Shock and Vibration, 2019 Fault diagnosis of rotating machinery mainly includes fault feature extraction and fault classification. Vibration signal from the operation of machinery usually could help diagnosing the operational state of equipment.
Lei You +5 more
doaj +1 more source
Fault detection and classification with the rebmix R package
Computers & Industrial Engineering, 2023 Fault detection and classification is an important part of assessing the structural and system health status. The classification and detection of faults and faulty units is mostly done with statistical methods. After the data are measured and collected, the use of statistical software is necessary.
Marko Nagode +3 more
openaire +3 more sources
Real-time fault diagnosis and fault-tolerant control [PDF]
, 2015 This "Special Section on Real-Time Fault Diagnosis and Fault-Tolerant Control" of the IEEE Transactions on Industrial Electronics is motivated to provide a forum for academic and industrial communities to report recent theoretic/application results in ...
Cecati, Carlo +2 more
core +1 more source