Abstract
In electrical engineering, partial discharge (PD) measurement has been widely used for inspecting and judging insulation conditions of high voltage (HV) apparatus. However, on-site PD measurement easily becomes contaminated by noises. Particularly, sinusoidal noise makes it difficult to recognize real PD signal, thus leading to the misjudgment of insulation conditions. Therefore, sinusoidal noise removal is necessary. In this paper, instantaneous frequency (IF) is introduced, and the synchrosqueezing transform (SST) as well as singular spectrum analysis (SSA) is proposed for sinusoidal noise removal. A continuous analytic wavelet transform is firstly applied to the noisy PD signal and then the time frequency representation (TFR) is reassigned by SST. Narrow-band sinusoidal noise has fixed IF, while PD signal has much larger frequency range and time-varying IF. Due to the difference, the reassigned TFR enables the sinusoidal noise to be distinguished from PD signal. After synthesizing the signal with the recognized IF, SSA is further applied to signal refinement. At last, a numerical simulation is carried out to verify the effectiveness of the proposed method, and its robustness to white noise is also validated. After the implementation of the proposed method, wavelet thresholding can be further applied for white noise reduction.
Highlights
Partial discharge (PD) is a phenomenon that commonly occurs in various electrical apparatus such as power transformers, gas insulated switchgears, and cables
The Gaussian white noise is firstly added to pure PD signal with the signal to noise ratio (SNR) set to be −2.2, and the sinusoidal noise is added
In order to study the performance of the proposed method, we decide to set the frequency of one sinusoid closer to the band of frequencies corresponding to the pure PD
Summary
Partial discharge (PD) is a phenomenon that commonly occurs in various electrical apparatus such as power transformers, gas insulated switchgears, and cables. The short-time Fourier transform (STFT) [26] It cannot accurately represent the frequency information of signals. Nonsinusoidal signals include pure PD signal and white noise In term of this difference, it is proposed to distinguish sinusoidal noise based on SST in this paper. After extraction of TFR with a specific IF through the inverse SST, a synthetic signal is obtained This synthetic signal greatly reduces the energy of pure PD signal and white noise and can be regarded as the sum of the original sinusoid with the same IF and the residue.
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