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Micro-vibration signal clustering method and device based on improved K-means

A signal clustering and microseismic technology, which is applied in seismic signal processing, measuring devices, seismology, etc., can solve problems such as signal distortion and affecting the waveform shape of microseismic signals, and achieve the effect of good reliability and high processing efficiency

Active Publication Date: 2021-03-19
XINWEN MINING GROUP
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Problems solved by technology

Interference noise from external environmental factors such as mine blasting and mechanical vibration will also affect the waveform shape of the microseismic signal to a certain extent, resulting in signal distortion

Method used

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  • Micro-vibration signal clustering method and device based on improved K-means
  • Micro-vibration signal clustering method and device based on improved K-means
  • Micro-vibration signal clustering method and device based on improved K-means

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Embodiment 1

[0091] refer to Figure 4-6 As shown, firstly, 200 microseismic signals are randomly selected in the mining area, and the waveform diagram of each microseismic signal is similar to Figure 4 shown. Each microseismic signal waveform is actually a set of time series composed of thousands of sampling points.

[0092] Each microseismic signal is converted into a vector form by the DTW vectorizer and stored in the form of X 1 ,X 2 ,X 3 ,...,X n . The DTW vectorizer will pass these vectors back to the K-means control machine for storage. According to the number of clusters K, designate K sample microseismic signal vectors as the initial cluster center vector T 1 , T 2 ,...,T k .

[0093] Then, each microseismic signal X i with each cluster center T k Calculate the DTW distance matrix through the DTW stripper, such as Figure 7 shown in X 1 ,X 2 ,X 3 ,...,X n and cluster center T 1 For example: get the distance matrix Y respectively 11 ,Y 21 ,...,Y n1 . with mat...

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Abstract

The invention discloses a micro-vibration signal clustering method and device based on improved K-means, and the method comprises the following steps: S1, transmitting a micro-vibration signal to a K-means control machine, and generating sample data and an initial clustering center; s2, calculating a DTW distance between the sample data and an initial clustering center; s3, comparing DTW distances, carrying out first clustering after labels are marked, transmitting a result obtained through the first clustering to a DBA updater, and obtaining a new clustering center; s4, comparing whether theinitial clustering center is equal to the updated clustering center or not, if yes, executing the step S5, and if not, executing the step S6; s5, outputting a clustering result; and S6, returning to the step S3-S4, and carrying out next clustering. The method and device are more suitable for micro-seismic signal clustering analysis, waveform characteristics are reserved to the maximum extent, andthe method and device are high in processing efficiency and good in reliability.

Description

technical field [0001] The invention relates to the technical field of data mining, in particular to a microseismic signal clustering method and device based on improved K-means. Background technique [0002] In the process of coal mine production, there are usually roof and floor fractures, pressure relief and excavation blasting, all of which cause the rock mass to be affected by external forces and release energy to produce vibrations that last for a period of time. Usually, shock waves with a vibration frequency less than 100 Hz and an event energy in the range of 103 to 1011 J are called microseisms. The microseismic signals generated during the deformation and fracture of coal and rock have the characteristics of short time and rapid mutation. The interference noise of external environmental factors such as mine blasting and mechanical vibration will also affect the waveform shape of the microseismic signal to a certain extent, resulting in signal distortion. In summ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G01V1/28
CPCG01V1/288G06F18/22G06F18/23213
Inventor 丁琳琳张明潘一山孙明馨陈泽刘媛媛刘丽侯俊敏
Owner XINWEN MINING GROUP
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