A Wavelet Based Tool to Assist the Automated Analysis of Waveform Disturbances Records in Power Generators

This paper presents an automated disturbance analysis scheme for electrical power generating units. It proposes a method based on wavelet transform applied to transient (waveform) records of disturbances. The objectives are to detect faults in generators, perform a segmentation of the records and extract information that characterize the faults. The output of the method is a set of representative information of the monitored signals, which can be used in a classification system for automated fault diagnosis. The large volume of data produced by the digital recorders of power system disturbances justifies the search for automated analysis methods that can be employed to assist the utilities engineers. Tests were conducted to determine the best mother wavelet in the segmentation process. The proposed method was applied to five case studies with real disturbance data and the obtained results confirmed its efficiency.