Terminal Waveform Similarity Measurement Method Based on the Improved Dynamic Time Warping Algorithm

The dynamic time warping algorithm (DTW) has problems such as high computational complexity and “ill-conditioned matching.” Aiming at the above two main problems, this paper proposes an improved DTW algorithm for the final wave recording of the primary and secondary deep fusion equipment detection p...

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Bibliographic Details
Published in:Mathematical problems in engineering 2022-11, Vol.2022, p.1-14
Main Authors: Yang, Xiong, Guo, Jiahao, Zhang, Xuhui, Zhu, Chenyang
Format: Article
Language:English
Subjects:
Algorithms
Communication
Efficiency
Electric power distribution
Entropy
Matching
Measurement methods
Planning
Random noise
Signal processing
Similarity
Similarity measures
Time series
Warping
Waveforms
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Summary:The dynamic time warping algorithm (DTW) has problems such as high computational complexity and “ill-conditioned matching.” Aiming at the above two main problems, this paper proposes an improved DTW algorithm for the final wave recording of the primary and secondary deep fusion equipment detection platform. The terminal recorded waveform and the waveform with non-Gaussian noise added as the research object, the two sets of waveforms are divided into frames and windowed, and the short-term energy entropy ratio of the two sets of waveforms is input into the DTW as the test vector. Using the optimal matching paths and distances of the two input vectors, the common substring lengths of the two sets of short-term energy entropy ratio sequences are calculated. Then, we define the optimal matching coefficient and correct the waveform similarity. The experimental data show that the improved DTW algorithm can accurately quantify the similarity between terminal waveforms, which can provide effective data support for the health status assessment of power distribution terminals.
ISSN:1024-123X
1563-5147
DOI:10.1155/2022/2180550