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International Journal of Multimedia Computing, 2022, 3(4); doi: 10.38007/IJMC.2022.030405.

Seismic Signal Adaptive Endpoint Detection Based on Human-Computer Interaction


Yue Wang

Corresponding Author:
Yue Wang

Hebei Agricultural University, Baoding, China


With the development of artificial intelligence technology, robot technology has become more mature, and human-computer interaction technology has become more widely used. China is a country with frequent earthquakes. The application of robot technology to seismic signal detection is of great significance to solve various problems in earthquake disasters. The research purpose of this paper is to study adaptive endpoint detection of seismic signals based on human-computer interaction technology. Based on the analysis of adaptive noise reduction of signal autocorrelation function, this paper references the concept of autocorrelation similarity distance, and proposes human-machine interaction technology Seismic signal adaptive endpoint detection, discusses the description of noise and noisy signals based on autocorrelation similarity distance, and summarizes the adaptive endpoint detection method of seismic signals based on human-computer interaction technology, and gives the specific implementation of the algorithm Compared with the experimental detection results obtained by this method and the time-domain waveform envelope and the method of manually detecting the time-table seismic signal endpoint detection, the research results in this paper show that the accuracy of this algorithm is as high as 96.11%, Under the condition of noise ratio, the end position of the seismic signal can still be detected more accurately by using this algorithm.


Human-Computer Interaction Technology, Seismic Signals, Endpoint Detection, Autocorrelation Function, Adaptive Noise Reduction

Cite This Paper

Yue Wang. Seismic Signal Adaptive Endpoint Detection Based on Human-Computer Interaction. International Journal of Multimedia Computing  (2022), Vol. 3, Issue 4: 53-71. https://doi.org/10.38007/IJMC.2022.030405.


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