Results 21 to 30 of about 12,066 (353)
Machines, 2023 Direct current (DC) networks play a pivotal role in the growing integration of renewable energy sources. However, the occurrence of DC arc faults can introduce disruptions and pose fire hazards within these networks.
Hoang-Long Dang +2 more
doaj +1 more source
Classification of EMI discharge sources using time–frequency features and multi-class support vector machine [PDF]
, 2018 This paper introduces the first application of feature extraction and machine learning to Electromagnetic Interference (EMI) signals for discharge sources classification in high voltage power generating plants.
Boreham, Philip +5 more
core +2 more sources
Implementation of Oriented Filters for Arc Detection. [PDF]
Procedings of the British Machine Vision Conference 1995, 1995 This paper is concerned with the implementation of oriented Gaussiantype filters with several possible decomposition schemes, including the steerable approach and the wavelet transform. A novel spatial decomposition scheme is introduced, in which the filters are projected onto a set of Gaussian basis functions which are not dependent on the orientation
Oakley, JP, Wen, Y.
openaire +2 more sources
Arcing detection method of metro pantograph based on improved yolov4-tiny
机车电传动, 2023 Arcing on metro pantographs contribute to the accelerated wear of pantograph strips and the catenary, imposing a serious safety risk to rail transit. For the problem of strong light interference and variable background in pantograph arcing detection for ...
AI Shengyong +2 more
doaj
A Novel Fault Detection and Classification Approach in Transmission Lines Based on Statistical Patterns [PDF]
Iranian Journal of Electrical and Electronic Engineering, 2023 Symmetrical nature of mean of electrical signals during normal operating conditions is used in the fault detection task for dependable, robust, and simple fault detector implementation is presented in this work.
Das P. Chennamsetty, Sravana K. Bali
doaj
Imaging time series for the classification of EMI discharge sources [PDF]
, 2018 In this work, we aim to classify a wider range of Electromagnetic Interference (EMI) discharge sources collected from new power plant sites across multiple assets. This engenders a more complex and challenging classification task.
Boreham, Philip +5 more
core +2 more sources
DA-DCGAN: An Effective Methodology for DC Series Arc Fault Diagnosis in Photovoltaic Systems
IEEE Access, 2019 DC arc faults, especially series arcing, can occur in photovoltaic (PV) systems and pose a challenging detection and protection problem. Machine learning-based methods are increasingly being used for fault diagnosis applications. However, the performance
Shibo Lu +4 more
doaj +1 more source
Deep residual neural network for EMI event classification using bispectrum representation [PDF]
, 2018 This paper presents a novel method for condition monitoring of High Voltage (HV) power plant equipment through analysis of discharge signals. These discharge signals are measured using the Electromagnetic Interference (EMI) method and processed using ...
Boreham, Philip +5 more
core +2 more sources
Detection of electric arcs in large batteries
2013 World Electric Vehicle Symposium and Exhibition (EVS27), 2013 This paper addresses the precocious detection of electric arcs in an electric vehicle battery generated by a connector fault. The detection principle is based on the acoustic emission of the arc. First, the identification of the electric arc acoustic signature as well as disturbances in the environment of detection has been realized.
Cattin, V. +4 more
openaire +1 more source
Research on the Switching Arc Loss of on-Load Tap Changer
IEEE Access, 2019 The on-load tap changer (OLTC) switching arc will affect the life of the contact, so it is necessary to test its working condition. Based on DQ coordinate transformation, fundamental wave component extraction, and wavelet algorithm, proposed an OLTC arc ...
Dongdong Song +4 more
doaj +1 more source