DocumentCode :
1706908
Title :
Application of Improved Mathematical Morphology Method in the Power Quality Monitoring
Author :
Sen, Ouyang ; Zhen, Ren
Author_Institution :
Coll. of Electr. Power, South China Univ. of Technol., Guangzhou
fYear :
2006
Firstpage :
1
Lastpage :
6
Abstract :
By means of the mathematical morphology (MM) method, the power quality (PQ) disturbance signals can be monitored quickly and effective. However, the signal under investigation is often corrupted by noises, and the MM filter formed by fixed structure elements of can not handle this very well. In this paper, the theory and shortage of traditional MM theory are analyzed at first. And an improved MM (IMM) method is proposed. In this method, appropriate structural elements are selected and different structural elements and their self-adaptive weighted combinations are used to deal with perturbation signals. Also, the threshold method was used for reference, and it can improve the de-noising capability of the IMM method. In this way, the IMM method can carry out the de-noising and disturbance location task. Simulated results and practical application show that the proposed IMM method is practicable and possessed the advantages of simplicity, high calculation speed and easy hardware implementation.
Keywords :
mathematical morphology; power system faults; fixed structure elements; mathematical morphology; power quality disturbance signals; power quality monitoring; self-adaptive weighted combinations; Degradation; Mean square error methods; Monitoring; Morphology; Noise reduction; Power quality; Power systems; Signal processing; Signal processing algorithms; Voltage fluctuations; de-noising; mathematical morphology; power quality; power system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power System Technology, 2006. PowerCon 2006. International Conference on
Conference_Location :
Chongqing
Print_ISBN :
1-4244-0110-0
Electronic_ISBN :
1-4244-0111-9
Type :
conf
DOI :
10.1109/ICPST.2006.321769
Filename :
4116187
Link To Document :
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