Name
Title | ||
|---|---|---|
Research on Power Quality Disturbance Signal Classification Based on Random Matrix Theory. |
Abstract | ||
|---|---|---|
In this paper, a method of power quality disturbance classification based on random matrix theory (RMT) is proposed. The method utilizes the power quality disturbance signal to construct a random matrix. By analyzing the mean spectral radius (MSR) variation of the random matrix, the type and time of occurrence of power quality disturbance are classified. In this paper, the random matrix theory is used to analyze the voltage sag, swell and interrupt perturbation signals to classify the occurrence time, duration of the disturbance signal and the depth of voltage sag or swell. Examples show that the method has strong anti-noise ability. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-981-10-6388-6_30 | Communications in Computer and Information Science |
Keywords | Field | DocType |
Power quality disturbance,Random matrix theory,Mean spectral radius | Interrupt,Spectral radius,Pattern recognition,Algorithm,Signal classification,Artificial intelligence,Swell,Voltage sag,Mathematics,Perturbation (astronomy),Random matrix,Power quality | Conference |
Volume | ISSN | Citations |
728 | 1865-0929 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ke-yan Liu | 1 | 1 | 2.44 |
| Dongli Jia | 2 | 0 | 1.01 |
| Kaiyuan He | 3 | 1 | 1.09 |
| tingting zhao | 4 | 20 | 6.45 |
| Fengzhan Zhao | 5 | 0 | 0.34 |