Classification of Power Quality Disturbance Signals Using FFT, STFT, Wavelet Transforms and Neural Networks - A Comparative Analysis

Devi, M. Indra; Rajaram, D.R.; Selvakuberan, K.

doi:10.1109/iccima.2007.279

Cited by 22 publications

(8 citation statements)

References 3 publications

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“…The FFT transforms signals of a temporal domain into a frequency domain. However, the FFT is restricted in evaluating the frequency component for the desired time point because of temporal limitations [16].…”

Section: Feature Namementioning

confidence: 99%

“…Hence, matching pursuit, which can generate signals using a small amount of data and enables quick data generation using a relatively simple formula compared with other data generation techniques, was employed in this study. The matching pursuit algorithm was first introduced by Mallat and Zhang [16]. The basic idea of matching pursuit is to first select atoms individually to identify the atom with the highest inner product using the current signal after expressing signals with approximation, subtracting an approximation that uses only that one atom from the signal, and repeating the process until the residual signal is decomposed.…”

Section: Data Increase Using Matching Pursuitmentioning

confidence: 99%

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Study on Noise Reduction and Data Generation for sEMG Spectrogram Based User Recognition

Kim

Pan

2022

Applied Sciences

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With the spread of the modern media industry, harmful genre contents are indiscriminately disseminated to teenagers. The password identification method used to block sensational and violent genre content has become a problem that teenagers can easily steal. Therefore, a user identification method with less risk of theft and hacking is required. The surface EMG (sEMG) signal, which is an electrical signal generated inside the body and has individual features, is being studied as a next-generation user identification method. sEMG involves measuring an individual’s unique muscular strength activated over time as digital signals, thus giving it the advantage of generating different signal patterns. However, it is difficult to constantly and repeatedly acquire each motion signal and the number of repetitions for each motion is insufficient, thus there is a limit to improving user identification accuracy. In this paper, we propose a user identification system that solves the problem of insufficient data by applying the matching pursuit that enables signal generation to the sEMG signal from which the resting signal has been removed and improves classification accuracy by extracting STFT-based time–frequency features. As a result of the experiment, the user identification accuracy of the sEMG spectrogram with the resting state signal removed was 85.4%. In addition, when the training data were increased through data generation, the accuracy was improved, showing a user identification accuracy of 96.1%. Improved user recognition accuracy was confirmed when the training data of the sEMG signal from which the resting signal was removed were increased and multidimensional features including time–frequency were used.

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Section: Feature Namementioning

confidence: 99%

Section: Data Increase Using Matching Pursuitmentioning

confidence: 99%

Study on Noise Reduction and Data Generation for sEMG Spectrogram Based User Recognition

Kim

Pan

2022

Applied Sciences

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“…FFT enables the transformation of a signal in time domain to frequency domain. However, the FFT method does not support analyses of the frequency components at the point of the desired time owing to its temporal limitations [22].…”

Section: Related Workmentioning

confidence: 99%

User Recognition System Based on Spectrogram Image Conversion Using EMG Signals

Kim¹,

Choi²,

Kim³

et al. 2022

Computers, Materials &Amp; Continua

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Recently, user recognition methods to authenticate personal identity has attracted significant attention especially with increased availability of various internet of things (IoT) services through fifth-generation technology (5G) based mobile devices. The EMG signals generated inside the body with unique individual characteristics are being studied as a part of nextgeneration user recognition methods. However, there is a limitation when applying EMG signals to user recognition systems as the same operation needs to be repeated while maintaining a constant strength of muscle over time. Hence, it is necessary to conduct research on multidimensional feature transformation that includes changes in frequency features over time. In this paper, we propose a user recognition system that applies EMG signals to the short-time fourier transform (STFT), and converts the signals into EMG spectrogram images while adjusting the time-frequency resolution to extract multidimensional features. The proposed system is composed of a data pre-processing and normalization process, spectrogram image conversion process, and final classification process. The experimental results revealed that the proposed EMG spectrogram image-based user recognition system has a 95.4% accuracy performance, which is 13% higher than the EMG signal-based system. Such a user recognition accuracy improvement was achieved by using multidimensional features, in the time-frequency domain.

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“…В качестве основного метода измерения уровней гармонических составляющих сигналов токов и напряжений должен применяться метод на базе дискретного преобразования Фурье (ДПФ) (МЭК 61000-4-7). Однако, как указано в [2,3], данное преобразование крайне чувствительно к некратности интервала наблюдения и измеряемых составляющих. Для устранения этого недостатка в средствах измерения предусмотрена синхронизация частоты квантования по отношению к частоте основной гармоники измеряемого сигнала, а также объединение гармонических групп.…”

Section: анализ литературных данных и постановка проблемыunclassified

Measuring equipment syncronisation problems while power quality conformity assessment

Гриб

Гапон

Жданов³

et al. 2014

EEJET

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У статті розглянуто питання недоліків існуючих нормативних документів, що регламентують побудову вимірювальних засобів для оцінки відповідності якості електричної енергії по такому параметру, як рівні вищих гармонійних складових. Наведено експериментальні дані та їх аналіз, що говорять про неможливість виконання оцінки за класом А з буквальним виконанням стандартів Ключові слова: вищі гармоніки, синхронізація, якість, електрична енергія, частота, енергосистема, споживач В статье рассмотрен вопрос недостатков существующих нормативных документов, регламентирующих построение измерительных средств для оценки соответствия качества электрической энергии по такому параметру, как уровни высших гармонических составляющих. Приведены экспериментальные данные и их анализ, говорящие о невозможности выполнения оценки по классу А с буквальным выполнением стандартов Ключевые слова: высшие гармоники, синхронизация, качество, электрическая энергия, частота, энергосистема, потребитель

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Classification of Power Quality Disturbance Signals Using FFT, STFT, Wavelet Transforms and Neural Networks - A Comparative Analysis

Cited by 22 publications

References 3 publications

Study on Noise Reduction and Data Generation for sEMG Spectrogram Based User Recognition

Study on Noise Reduction and Data Generation for sEMG Spectrogram Based User Recognition

User Recognition System Based on Spectrogram Image Conversion Using EMG Signals

Measuring equipment syncronisation problems while power quality conformity assessment

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