Power quality classification based on rough set and wavelet transform
Min Shi · Dianli zidonghua shebei · 2005
A method combining wavelet transform with rough set is proposed to avoid the complex judgment and heavy computation of common power quality classification methods.The continuous eigenvector sample data of disturbance signal is extracted by wavelet transform and then dispersed by fuzzy C-means clustering algorithm to achieve a rule table of classification knowledge.By using the attributes and attribute values reducing algorithm of rough set theory,the core rule knowledge is finally obtained for power quality classification.Experiment is carried out with the simulative signal data generated by Matlab and results show that the proposed method classifies the signal types straight and simply.