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- W2559899958 abstract "To investigate the remote detecting approaches of weak transient electromagnetic signals, the detecting method based on the general cross correlation and chaotic time series prediction integrate algorithm is proposed. Based on the double antennas test and cross correlation information estimation, the signal detection of weak non-periodic discharge signal in low Signal to Noise Ratio (SNR) is transformed to the estimation of periodic time- delay parameters, which decreases the level of noise simultaneously. The results of estimation are predicted based on chaotic predicting method, and the mean value of predicting error is the detection results of target signal. The feasibility of the approach is analyzed by simulating and experimental method. The results show that in the low SNR, the integration method can effectively restrain the interference from noise. Compared with the traditional cross correlation method or chaotic prediction algorithm, the detecting probability is higher for weak transient electromagnetic signals. Furthermore, the pulse integrating algorithm needs the less accumulation times, and its detecting efficiency increases. Hence, the proposed integrate algorithm is suitable for remote detection of partial discharge source." @default.
- W2559899958 created "2016-12-16" @default.
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- W2559899958 date "2015-01-01" @default.
- W2559899958 modified "2023-09-27" @default.
- W2559899958 title "Detection of Weak Transient Electromagnetic Signals Based on Generalized Cross Correlation and Chaotic Time Series Prediction Integrate Algorithm" @default.
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