A gas source declaration scheme based on a tetrahedral sensor structure in three-dimensional airflow environments.

A gas source declaration scheme based on a tetrahedral sensor structure in three-dimensional airflow environments is proposed. First, a tetrahedral sensor structure was established. Based on the tetrahedral structure, the gas source declaration problem was converted into a two-class classification issue. Then a classification algorithm combining an extreme learning machine (ELM, a fast neural network classifier) with a gas mass flux criterion is proposed. A novel calculation method for the mass flux through a closed tetrahedral surface is presented, and a mass flux criterion was developed which acts as a training sample filter for the ELM. The source declaration scheme was validated by using both regular and irregular tetrahedron experiments.

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