Fault line detection method based on the improved SVD de-noising and ideal clustering curve for distribution networks

This study proposes an adaptive fault line detection method based on the improved singular value decomposition (SVD) de-noising and ideal clustering curve for distribution networks. First, the improved SVD algorithm is introduced to obtain the pure transient zero sequence current. Then, the fast Fourier transformation is employed to analyse the baseband signal and calculate the phase differences. After that, if the difference values are larger than the set threshold, the detection method based on the improved SVD and ideal clustering curve of baseband components is proposed; if not, the 1/4 cycle damping non-periodic components are rearranged, then based on the first half waveform extreme values and the rearranging damping non-periodic components, the detection method based on the ideal clustering curve of damping components is introduced. The simulation results prove the correctness of proposed selection method. After comparing with the existing methods, the advantages of proposed method are confirmed.

[1]  Jie Gao,et al.  An adaptive fault detection method based on atom sparse and evidence fusion for the small current to ground system , 2018, Trans. Inst. Meas. Control.

[2]  Xiangjun Zeng,et al.  Research on multi-terminal traveling wave fault location method in complicated networks based on cloud computing platform , 2017 .

[3]  Liu Xing-yan,et al.  Study on higher order wavelet packet singular entropy and its application to faulty line selection , 2011 .

[4]  Dusmanta Kumar Mohanta,et al.  Transmission line fault detection and localisation methodology using PMU measurements , 2015 .

[5]  Wufan Chen,et al.  Adaptive Denoising by Singular Value Decomposition , 2011, IEEE Signal Processing Letters.

[6]  Teymoor Ghanbari,et al.  k-NN based fault detection and classification methods for power transmission systems , 2017, Protection and Control of Modern Power Systems.

[7]  M. Dehghani,et al.  Fast fault detection and classification based on a combination of wavelet singular entropy theory and fuzzy logic in distribution lines in the presence of distributed generations , 2016 .

[8]  Tommy W. S. Chow,et al.  Binary- and Multi-class Group Sparse Canonical Correlation Analysis for Feature Extraction and Classification , 2013, IEEE Transactions on Knowledge and Data Engineering.

[9]  Hongchun Shu,et al.  Automated double-ended traveling wave record correlation for transmission line disturbance analysis , 2016 .

[10]  Xiangning Lin,et al.  Zero-sequence compensated admittance based faulty feeder selection algorithm used for distribution network with neutral grounding through Peterson-coil , 2014 .

[11]  Meng Joo Er,et al.  Sequential fuzzy clustering based dynamic fuzzy neural network for fault diagnosis and prognosis , 2016, Neurocomputing.

[12]  Sun Haifeng An Algorithm for Electrical Harmonic Analysis Based on Triple-spectrum-line Interpolation FFT , 2012 .

[13]  Flavio B. Costa Fault-Induced Transient Detection Based on Real-Time Analysis of the Wavelet Coefficient Energy , 2014 .

[14]  Zhao Xing-bing,et al.  A New Approach to Detect Fault Line in Resonant Earthed System Using Simulation After Test , 2008 .

[15]  Ren Zhilin Fault line selection of distribution network based on improved Hilbert-Huang Transform and identification confidence degree , 2015 .

[16]  Boying Wen,et al.  An adaptive fault line selection method based on atomic comprehensive measure values for distribution network , 2017 .

[17]  Piao Zailin,et al.  Fault line detection in neutral point ineffectively grounding power system based on phase-locked loop , 2014 .

[18]  Liu Yuge,et al.  Comprehensive Fault Line Selection Method for Resonant Grounded System Combining Wavelet Packet Transform with Fifth Harmonic Method , 2015 .

[19]  Konstantinos C. Gryllias,et al.  Rolling element bearing fault detection in industrial environments based on a K-means clustering approach , 2011, Expert Syst. Appl..

[20]  Zhang Qingzhou A New Method for Fault Line Selection in Distribution System with Arc Suppression Coil Grounding with Square-wave Signal Injection , 2012 .

[21]  Xu Fei De-noising method for electrocardiograph of non-uniform noise distribution based on singular value decomposition and wavelet transform , 2009 .

[22]  Nien-Che Yang,et al.  Features-clustering-based earth fault detection using singular-value decomposition and fuzzy c-means in resonant grounding distribution systems , 2017 .

[23]  G. Marchesan,et al.  A morphological filtering algorithm for fault detection in transmission lines during power swings , 2015 .

[24]  Józef Jonak,et al.  Early fault detection in gearboxes based on support vector machines and multilayer perceptron with a continuous wavelet transform , 2015, Appl. Soft Comput..

[25]  Sunil K Jha,et al.  Denoising by Singular Value Decomposition and Its Application to Electronic Nose Data Processing , 2011, IEEE Sensors Journal.