Abstract
Partial discharge (PD) detection can effectively achieve the status maintenance of XLPE (Cross Linked Polyethylene) cable, so it is the direction of the development of equipment maintenance in power systems. At present, a main method of PD detection is the broadband electromagnetic coupling with a high-frequency current transformer (HFCT). Due to the strong electromagnetic interference (EMI) generated among the mass amount of cables in a tunnel and the impedance mismatching of HFCT and the data acquisition equipment, the features of the pulse current generated by PD are often submerged in the background noise. The conventional method for the stationary signal analysis cannot analyze the PD signal, which is transient and non-stationary. Although the algorithm of Shannon wavelet singular entropy (SWSE) can be used to analyze the PD signal at some level, its precision and anti-interference capability of PD feature extraction are still insufficient. For the above problem, a novel method named Renyi wavelet packet singular entropy (RWPSE) is proposed and applied to the PD feature extraction on power cables. Taking a three-level system as an example, we analyze the statistical properties of Renyi entropy and the intrinsic correlation with Shannon entropy under different values of α . At the same time, discrete wavelet packet transform (DWPT) is taken instead of discrete wavelet transform (DWT), and Renyi entropy is combined to construct the RWPSE algorithm. Taking the grounding current signal from the shielding layer of XLPE cable as the research object, which includes the current pulse feature of PD, the effectiveness of the novel method is tested. The theoretical analysis and experimental results show that compared to SWSE, RWPSE can not only improve the feature extraction accuracy for PD, but also can suppress EMI effectively.
Highlights
The internal partial discharge (PD) of XLPE cable refers to a phenomenon of discharge that takes place in the insulating structure of XLPE cable in a power system
The research suggests that due to the electromagnetic interference caused by the mass amount of cables in the tunnel, with the impedance mismatching between high frequency current transformer (HFCT) and the data acquisition equipment, the signal features of the pulse current produced by PD are often submerged by background noise, and the detection results processed by software and hardware are still not good enough
Consideringthe short durationand low energy of the pulse current caused by PD and electromagnetic interference (EMI), in this paper, based on the combination of discrete wavelet packet transform (DWPT) and Renyi entropy, a novel method using Renyi wavelet packet singular entropy (RWPSE) is proposed, and it is applied to the PD feature extraction
Summary
The internal partial discharge (PD) of XLPE cable refers to a phenomenon of discharge that takes place in the insulating structure of XLPE cable in a power system. The sampling of the PD signal mainly uses the broadband electromagnetic coupling method in which a high frequency current transformer (HFCT) is used to sample the pulse current from the cable shielding layer to the ground when PD takes place. As an analysis method of a non-stationary signal, Shannon wavelet singular entropy (SWSE) has been applied in transient signal feature extraction gradually, and some interesting results have been obtained [1]. Consideringthe short durationand low energy of the pulse current caused by PD and electromagnetic interference (EMI), in this paper, based on the combination of DWPT and Renyi entropy, a novel method using Renyi wavelet packet singular entropy (RWPSE) is proposed, and it is applied to the PD feature extraction. The effectiveness of the method is proven by theoretical analysis and experiments
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