jesperiksson / struc-mon

Toolbox for analyzing bridges using ANN and other methods

struc-mon

Linux

Downloads and setup

1. Clone this repository into the desired folder: git clone https://github.com/jesperiksson/struc-mon .
2. Make sure you have at least Python 3.7 installed: ´python --version´. Othervise update: https://docs.python-guide.org/starting/install3/linux/
3. Make sure you either have Anaconda installed: https://docs.anaconda.com/anaconda/install/ or have the following packages installed: Matplotlib.pyplot - For plots
   Numpy - For maths
   Pandas - For data frames
   Rainflow - For creating rainflow analysis of stress
   SciPy - For signal analysis
   sklearn - For normalization
   Tensorflow 2.x - For machine learning \ Otherwise they can be installed using pip:
   pip install pip
   Matplotlib: https://pypi.org/project/matplotlib/
   Numpy: https://numpy.org/install/
   Pandas: https://pypi.org/project/pandas/
   Rainflow: https://pypi.org/project/rainflow/
   SciPy: https://www.scipy.org/install.html
   sklearn: https://scikit-learn.org/stable/install.html
   Tensorflow: https://www.tensorflow.org/install/pip \
4. Open the file in the repo named config.py and provide the path to the folder where the measurement files are stored in the variable file_path, e.g. file_path = 'home/user/measurements'

Data.py

Superclass for objects containing data

AggregatedData.py

Subclass containing methods for reading and storing data using OGC Standard: http://docs.opengeospatial.org/is/15-078r6/15-078r6.html

PostgresData.py

Subclass containing methods for reading and storing data from a PostgreSQL server. Queries are generated with a QueryGenerator object. Also contain a further subclass for anomalies.

Anomaly.py

Anomaly objects

AnomalySettings.py

Settings for anomaly objects

Model.py

Superclass for model objects. Also contains subclasses TimeSeriesPredictionNeuralNet and TimeSeriesClassificationNeuralNet

PCAAnomalies

Class for PCA objects operating on Anomaly objects