Feature extraction of On-Load Tap-Changer Based on Improved EMD Energy Spectrum

Wenquan, Huang

doi:10.1051/e3sconf/202015501006

Cited by 5 publications

(2 citation statements)

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“…Specific measurement systems have been developed to investigate patterns of vibration signals during the switching. Most commercial instrumentation uses electrical accelerometers installed in the equipment tank [2] - [3]. The signals obtained by these sensors have a low signal-noise ratio in high voltage environments due to the cross-sensitivity with other electromagnetic sources inherent to this type of installation [4].…”

Section: Introductionmentioning

confidence: 99%

“…Among the existing methodologies for extracting features, the technique to analyze typical signal signatures in the time domain is highlighted [2]. On the other hand, several methods use features from the frequency spectrum to identify operational deviations [3] - [5]. The fiber Bragg grating (FBG) has some advantages compared to conventional sensors, such as: being chemically inert and immune to electromagnetic interference.…”

Section: Introductionmentioning

confidence: 99%

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Features Extraction for Classification in Switching Devices using Fiber Bragg Grating

Benetti

Dureck

Dreyer

et al. 2023

J. Microw. Optoelectron. Electromagn. Appl.

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Vibration analysis systems are used to assess the operational condition of machines and electromechanical components in various applications. This work presents a measurement and feature extraction system that analyzes dynamic strain patterns in signals measured by fiber Bragg grating (FBG). The features were used to identify different simulated operational conditions in an electromechanical relay. The selection of the best feature space in the first approach was performed by statistical criteria that determine the threshold values and frequency bands to calculate each signal's switching time and power spectral density (PSD). These parameters are used in the support vector machine (SVM) algorithm, which presents 98 % accuracy for distinguishing four distinct conditions. Another methodology for extracting features, called wavelet scattering transform (WST), was used to demonstrate that it is possible to achieve even better performance levels. The results allow extending the methodology to more complex systems.

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Section: Introductionmentioning

confidence: 99%