Analysis of Vehicle Signals in Multi-stations Seismic Data Based on Artificial Intelligence

Copyright (c) 2022 Zhengjie Zhang (zhangzhengjie@mail.ustc.edu.cn)

• This is the first part of the subject Analysis and association of vehicle signals in multi-station seismic data based on artificial intelligence.
• The second part of the subject belongs to the content of using convolutional neural networks to associate seismic signals. At present, the code is still being sorted out and has not been made public.
• The published data belongs to the test data.

Description

• K-Shape: K-Shape algorithm is used for clustering analysis to find the similarity of signals.
• xcorr: The cross-correlation test of the synthetic data and the cross-correlation results of the received signals of the actual stations.
• ObsPy-Tutorial.pdf: ObsPy Chinese tutorial -V 1.0 (2020/04/12), you can get more detailed use of ObsPy through the official website https://docs.obspy.org/

Installation

Via Anaconda (recommended):

• Create a new python virtual environment MLMSA and activate it

  conda create -n MLMSA python=3.8
  conda activate MLMSA
  

• Install the package

  (Note: We do not recommend that you install the package below the following version, the higher version is adapted.)

  conda install numpy==1.21.5 pandas==1.4.2 matplotlib==3.5.1 scipy==1.8.0 obspy==1.3.0
  

  If your installation fails, you can try to replace conda with pip. In addition, you can also try again after replacing Tsinghua or Ustc source

  conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
  conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge/ 
  conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/msys2/
  conda config --set show_channel_urls yes
  

  or

  conda config --add channels https://mirrors.ustc.edu.cn/anaconda/pkgs/main/
  conda config --add channels https://mirrors.ustc.edu.cn/anaconda/pkgs/free/
  conda config --add channels https://mirrors.ustc.edu.cn/anaconda/cloud/conda-forge/
  conda config --add channels https://mirrors.ustc.edu.cn/anaconda/cloud/msys2/
  conda config --add channels https://mirrors.ustc.edu.cn/anaconda/cloud/bioconda/
  conda config --add channels https://mirrors.ustc.edu.cn/anaconda/cloud/menpo/
  conda config --set show_channel_urls yes
  

Clone source codes

• Set your working directory at /data/

  cd /data/
  git clone https://github.com/zhangzj1209/MLMSA.git
  unzip MLMSA.zip
  cd MLMSA/
  

K-Shape

cd K-Shape/
python K_Shape.py

If you want to modify some basic parameters, it will be in ./config_KShape.py, and the parameters of the clustering algorithm are in the main function part of ./K_Shape.py.

The logging of K-Shape results are recorded in ./log.txt, loss function is recorded in ./Loss.npy, and the number of clusters is recorded in ./NUM_CLU.npy.

Then, you can use ./plot_KShape to show related figures.

xcorr

cd xcorr/

• run the example of synthetic data

  python synthetic_data.py
  

• run the result of field data

  python xcorr.py
  

  If you want to modify some basic parameters, it will be in ./config_xcorr.py.