Histogram-based thresholding in discrete wavelet transform for partial discharge signal denoising
المؤلف | Hussein, Ramy |
المؤلف | Shaban, Khaled Bashir |
المؤلف | El-Hag, Ayman H. |
تاريخ الإتاحة | 2022-12-21T10:01:47Z |
تاريخ النشر | 2015 |
اسم المنشور | 2015 International Conference on Communications, Signal Processing, and Their Applications, ICCSPA 2015 |
المصدر | Scopus |
الملخص | White noise is a major interference source that affects the partial discharge (PD) signal detection and recognition. Wavelet shrinkage denoising methods can efficiently reject the white noise embedded in the PD signal acquisition and measurement processes. The wavelet threshold determination is a key factor in the quality of noise suppression from signals. A novel threshold estimation technique, namely histogram-based threshold estimation (HBTE), is introduced to obtain the optimal level-dependent wavelet thresholds of noisy partial discharge signals. Unlike existing wavelet thresholding techniques, HBTE obtains two different threshold values for each wavelet subband. The proposed method is applied on measured PD signals at different noise levels. Experimental results show that the proposed thresholding approach outperforms the conventional threshold selection rules in terms of signal-to-noise ratio, cross correlation coefficient, root mean square error, and reduction in noise level. 2015 IEEE. |
راعي المشروع | Qatar National Research Fund |
اللغة | en |
الناشر | Institute of Electrical and Electronics Engineers Inc. |
الموضوع | Histogram-based threshold estimation (HBTE) Partial discharge signal Signalto-noise ratio (SNR) Wavelet threshold denoising |
النوع | Conference Paper |
الملفات في هذه التسجيلة
الملفات | الحجم | الصيغة | العرض |
---|---|---|---|
لا توجد ملفات لها صلة بهذه التسجيلة. |
هذه التسجيلة تظهر في المجموعات التالية
-
علوم وهندسة الحاسب [2284 items ]