A new study in maintenance for transmission lines based on independent component analysis

Authors:
Lijia Ren;Xiuchen Jiang;Gehao Sheng;Wu Bo
Affiliations:
Department of Electric Engineering, Shanghai Jiaotong University, Shanghai, China;Department of Electric Engineering, Shanghai Jiaotong University, Shanghai, China;Department of Electric Engineering, Shanghai Jiaotong University, Shanghai, China;Department of Electric Engineering, Shanghai Jiaotong University, Shanghai, China
Venue:
IMACS'08 Proceedings of the 7th WSEAS International Conference on Instrumentation, Measurement, Circuits and Systems
Year:
2008

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Abstract

It is important to monitor transmission towers and prevent increasingly common line break caused by human activity, in order to ensure the reliability and safety of the power grid operation. A new function is proposed to enhance the state maintenance of transmission lines. It relies on the monitoring of the high-voltage transmission towers to ensure the reliability and safety of the power grid operation. An approach which combines Independent Component Analysis (ICA) with neural network based on Particle Swarm Optimization (PSO) algorithm is presented to extract the vibration source signals caused by the destruction of the towers. The proposed algorithm separates the source vibration signals based on the FastICA. In order to distinguish the vibration pulse signal from other similar interference pulses, the algorithm of the feed forward neural network (FFNN) is used to identify the vibration pulses. Numerical results show that the algorithm is effective in extracting and identifying the vibration signals.