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A gas source declaration scheme based on a tetrahedral sensor structure in three-dimensional airflow environments
Hui-Rang Hou1, Yuan Tong1, Chao Ren1
1Tianjin Key Laboratory of Process Measurement and Control, School of Electrical and Information Engineering, Institute of Robotics and Autonomous Systems, Tianjin University, Tianjin 300072, China.
Abstract:
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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