论文信息 - Power quality detection and classification using wavelet-multiresolution signal decomposition

Power quality detection and classification using wavelet-multiresolution signal decomposition

The wavelet transform is introduced as a powerful tool for monitoring power quality problems generated due to the dynamic performance of industrial plants. The paper presents a multiresolution signal decomposition technique as an efficient method in analyzing transient events. The multiresolution signal decomposition has the ability to detect and localize transient events and furthermore classify different power quality disturbances. It can also be used to distinguish among similar disturbances.

[1] S. Santoso,et al. Power quality disturbance data compression using wavelet transform methods , 1997 .

[2] M. Wickerhauser,et al. Wavelets and time-frequency analysis , 1996, Proc. IEEE.

[3] W. E. Reid. Power quality issues-standards and guidelines , 1994 .

[4] W. Sweldens. Wavelets: What Next? , 1997 .

[5] Gerald T. Heydt,et al. Transient power quality problems analyzed using wavelets , 1997 .

[6] J. S. Mayer,et al. Wavelets and electromagnetic power system transients , 1996 .

[7] P. Pillay,et al. Application of wavelets to model short-term power system disturbances , 1996 .

[8] S. Santoso,et al. Power quality assessment via wavelet transform analysis , 1996 .

[9] John R. Williams,et al. Introduction to wavelets in engineering , 1994 .

[10] Hong-Ye Gao,et al. Wavelet analysis [for signal processing] , 1996 .

[11] John Douglas. Solving problems of power quality , 1993 .