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| An Improved Threshold Function Method for Power Quality Disturbance Signal De-Noising Based on Stationary Wavelet Transform |
| Fan Xiaolong1, 2, Xie Weicheng1, Jiang Wenbo1, Li Yi2, Huang Xiaoli1 |
1. School of Electrical and Information Engineering Xihua University Chengdu 610039 China;
2. State Grid Guangan Power Supply Company Guang’an 638000 China |
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Abstract The accurate detection and localization of mutation point information is the premise for analyzing power quality (PQ) disturbance signal with noise. But the mutation point feature must be retained during the signal de-noising. Accordingly, the stationary wavelet transform (SWT) is selected to decompose signals, and then the improved threshold function is proposed to de-noise signals. In addition, the noise mean square ( j is decomposition level) is estimated and the threshold could be calculated at each decomposition scale adaptively. According to the fact that the wavelet coefficients of signal and noise distribute on different scales, the proposed method exploits to amend the threshold. Finally the improved threshold function is used for PQ signal de-noising. Simulation results show that the proposed scheme can suppress the noise of PQ signal while keeping the mutation points well. The starting and ending time of the disturbance can be clearly observed from the treated wavelet coefficients, the transient oscillations and harmonic interference can also be distinguished.
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Received: 24 September 2014
Published: 28 July 2016
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2016, Vol. 31 
