Results 11 to 20 of about 2,214,988 (289)
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
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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 classification using an Artificial Neural Network based on Vibrations from a Reciprocating Compressor [PDF]
, 2010 Reciprocating compressors are widely used in industry for various purposes and faults occurring in them can degrade performance, consume additional energy, and even cause severe damage to the machine.
Gu, Fengshou, Ahmed, Mahmud
core +4 more sources
Journal of Electrical and Computer Engineering, 2021 In this paper, the multilevel classification model of high-speed railway signal equipment fault based on text mining technology is proposed for the data of high-speed railway signal fault.
Fan Gao +4 more
doaj +1 more source
A New Scheme for Fault Detection and Classification Applied to DC Motor
Trends in Computational and Applied Mathematics, 2018 This study presents an approach for fault detection and classification in a DC drive system. The fault is detected by a classical Luenberger observer. After the fault detection, the fault classification is started.
Laércio I. Santos +5 more
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Fault Classification of Reciprocating Compressor Based on Neural Networks and Support Vector Machines [PDF]
Reciprocating compressors play a major part in many industrial systems and faults occurring in them can degrade performance, consume additional energy, cause severe damage to the machine and possibly even system shut-down.
Gu, Fengshou +4 more
core +4 more sources
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
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
Machine fault diagnosis and condition prognosis using classification and regression trees and neuro-fuzzy inference systems [PDF]
, 2010 This paper presents an approach to machine fault diagnosis and condition prognosis based on classification and regression tress (CART) and neuro-fuzzy inference systems (ANFIS).
Yang, Bo-Suk, Tran, Van Tung
core +4 more sources
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