An Efficient Method for Optimizing Sensors' Layout for Accurate Measurement of Underground Ventilation Networks

Abstract

Due to the complex spatial hierarchy and large network scale of the mine ventilation system, it is difficult to obtain ventilation information of all branches in real-time, accurately, and comprehensively by arranging sensors. To overcome this difficulty, this paper proposes an optimal layout method of sensors based on the DETMAX algorithm and Tabu search algorithm. Given a known number of sensors, the proposed method can efficiently select an optimal set of branches to arrange these sensors according to the calculated airflow of each branch while considering both the air resistance error and the sensor error. This optimized sensor layout can minimize the airflow error of the undetected branches and obtain the ventilation information of the entire ventilation system accurately with a limited number of sensors. The proposed method has significant economic benefits and can provide technical support for developing intelligent ventilation systems. Finally, the performance and efficiency of this method are verified by comparing it with the Monte Carlo algorithm and the Ant Colony algorithm with data from the Wangjialing coal mine in China.