I am happy to announce the release of Earthing a python library for the design of electrical earthing networks. Currently only homogeneous earth is supported. It should be possible in the future to extent this to include two layer model using imaging techniques. Accuracy of the model needs to be compared against other commercial models for further improvements.
Features
- Earth grid design as per IEEE 80/ ENA_ER_S34
- Numerical earth network calculations using using boundary descretisation method.
- Evaluation of earth resistance of various earth electrode geometries.
- 3D plotting of electrode geometry used for design.
- 3D plotting of current density distribution for the earth network.
- 2D/3D plotting of surface potential distribution.
- Ploting and evaluation of mesh and step potentials.
Usage
Package is available on PyPI for installation (https://pypi.org/project/earthing). Use pip install earthing to install.
Program source includes detailed usage instructions for various functions and classes. Alternately project page has ipython notebooks covering typical use cases.
Dependencies
- Python 3
- Numpy
- Matplotlib
The article introduces Earthing, a Python library designed for electrical earthing network design, with features covering earth grid calculations, electrode geometry evaluation, numerical methods, and visualization of electrical properties. The combination of engineering calculations and Python programming makes the project an interesting example of how software libraries can support specialized technical applications.
ReplyDeleteThe library also makes extensive use of graphical analysis, including 2D and 3D plots of electrode geometry and electrical distributions. Learning Matplotlib Course can help developers understand how similar engineering data can be represented visually and interpreted more effectively.
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ReplyDeleteThe combination of numerical calculations and graphical analysis makes the project a useful example of processing technical data and presenting the results visually. These concepts can also inspire Image Processing Projects For Final Year, particularly where Python-based computation and visual analysis are important components.
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