Arc Fault Recognition Based on VMD and ELM

Liu, Shuxin; Liu, Zhenxing; Liu, Yang; Cao, Yundong; Li, Jing

doi:10.1007/978-981-33-6609-1_47

Cited by 2 publications

(3 citation statements)

References 1 publication

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“…The slots of rotor are particularly changed to obtain the necessary space harmonics in the case of speed estimation based on signal injection, and the saliency of the rotor position is identified by the algorithm of position estimation. For this, a closed loop observer model in combination with appropriate processing was utilized to track the rotor saliencies using a component of high-frequency voltage as the carrier signal [ 49 , 56 , 66 , [108] , [109] , [110] ]. Even while operating at low or no speed, the signal injection is still present.…”

Section: Rotor Saliencymentioning

confidence: 99%

“…There are two types of injection techniques: voltage and current [ 49 , 108 , 109 ]. As demonstrated in Fig.…”

Section: High-frequency Signal Injectionmentioning

confidence: 99%

“…has implemented disturbance observer as speed estimation algorithm. Which has been designed for low-speed range of 50–300 rpm [ 25 , 49 , 50 ].The second technique depends on machine saliency. Due to the ripple in the voltages and currents of stator caused by the modulation of reluctance brought on by existence of rotor slots is used to calculate the rotor speed.…”

Section: Introductionmentioning

confidence: 99%

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Review of speed estimation algorithms for three- phase induction motor

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Section: Rotor Saliencymentioning

confidence: 99%

“…There are two types of injection techniques: voltage and current [ 49 , 108 , 109 ]. As demonstrated in Fig.…”

Section: High-frequency Signal Injectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Review of speed estimation algorithms for three- phase induction motor

Elbarbary,

Al-Harbi,

Al-Gahtani

et al. 2024

MethodsX

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Series Arc Fault Diagnosis Based on Variational Mode Decomposition and Random Forest

et al. 2022

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In order to improve the accuracy of series arc fault detection and prevent fire accidents caused by series arc fault, a series arc fault simulation experiment circuit was built to obtain the low-frequency and high-frequency current waveform of series arc fault under different loads. The kurtosis, waveform factor, crest factor, pulse factor, and margin factor of low-frequency current waveform are extracted in the time domain. In the frequency domain, a method based on variational mode decomposition and energy entropy is proposed to extract the characteristic quantity of series arc faults. It was found that the energy entropy of the intrinsic mode function component with the largest variance contribution ratio will increase when a series of arc faults occur, and it was used as a characteristic quantity. Characteristic vectors were constructed based on time–frequency characteristic quantities, and the characteristic vector was trained based on the random forest algorithm to obtain the diagnosis model and analyze the series arc fault diagnosis. The analysis showed that the diagnostic accuracy of the model trained by the proposed method was above 97%, and the fault recognition effect was remarkable, which provides an important reference for the improvement of the series arc fault detection technology.

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Arc Fault Recognition Based on VMD and ELM

Cited by 2 publications

References 1 publication

Review of speed estimation algorithms for three- phase induction motor

Review of speed estimation algorithms for three- phase induction motor

Series Arc Fault Diagnosis Based on Variational Mode Decomposition and Random Forest

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