Abstract
Recent interest in line-tracking methods using UAV has been introduced in the research of pattern recognition and diagnosis of transmission system. A fault diagnosis method for transmission line based on Scale Invariant Feature Transform (SIFT) is proposed in this paper, which recognizes fault images by comparing aerial images with model images. The reliability and efficiency of the system is effectively improved by pro-calculating local scale-invariant features of models. The research can provide a new method for predictive maintenance of the transmission line.
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Yan, S., Jin, L., Zhang, Z., Zhang, W. (2013). Research on Fault Diagnosis of Transmission Line Based on SIFT Feature. In: Guo, C., Hou, ZG., Zeng, Z. (eds) Advances in Neural Networks – ISNN 2013. ISNN 2013. Lecture Notes in Computer Science, vol 7952. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39068-5_68
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DOI: https://doi.org/10.1007/978-3-642-39068-5_68
Publisher Name: Springer, Berlin, Heidelberg
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