seismic-detection

Mission

Planetary seismology missions struggle with the power requirements necessary to send continuous seismic data back to Earth. But only a fraction of this data is scientifically useful. Therefore we created a solution which would allow the lander to distinguish signals from noise, and send back only the data which matters.

Discarded solutions, why?

• Single Window Maeda-AIC (SWM-AIC) algorithm, did not fit our 1C data well since it is more sueful for 3C
• LTA/STA triggering, was found to be unrealiable at cutting through the noise in the raw data
• Machine Learning Model, considered unreliable by NASA and ourselves - which is why we went with a deterministic solution

How to setup the project

Prerequisites

• Python 3.9 or higher
• Jupyter Notebook
• Seismic data packages from NASA

1. Clone the repo by running the following command in your terminal

git clone https://github.com/Adrian2901/seismic-detection.git

2. Cd into the project directory

cd seismic-detection

4. Unzip the seismic data packages into the project directory
5. Install the dependencies

# Optional: Create a virtual environment
pip install -r requirements.txt

Project Structure

The project structure should look like this

.
├───space_apps_2024_seismic_detection # Directory which contains data from the NASA missions
│   └───data
│       ├───lunar
│       └───mars
│           ├───test
│           └───training
│               ├───catalogs
│               ├───data
│               └───plot
├── discard # Directory which contains old test files
│   ├── csv-plotting.py
│   ├── filter-test.ipynb
│   ├── ltasta.ipynb
│   ├── mseed-plotting.py
│   ├── plotting.ipynb
│   └── testing_ai.py
├── output # Directory which contains the output mSEED files
│   └── catalog.csv # This file contains the output of our algorithm
├── filter.py # Main filter algorithm
├── LICENSE
├── README.md
└── requirements.txt

How to run the project

To run this algorithm, we recommend to follow the steps detailed in detect.ipynb. There are four main sections in this notebook: Import depedencies, Select the dataset, Detect and plot seismic events, export detected seismic events.

Contributors

Full name	Email address	GitHub
Adrian Hassa	[email protected]	@Adrian2901
Marko Mojsov	[email protected]	@Flam30
Ionel Pop*	[email protected]	@IonelPopJara