AI Article Synopsis
- - The study focuses on improving intelligent ventilation systems by optimizing the monitoring of airflow using minimal sensors through a new concept called "independent cut set."
- - The research was conducted in a coal mine, demonstrating that setting up wind speed sensors in fewer than 30% of the tunnels was sufficient to accurately reconstruct airflow throughout the entire network.
- - The algorithm developed proved effective, as it successfully matched the reconstructed air volume to the actual airflow, providing a theoretical framework for efficient airflow reconstruction in ventilation systems.
Article Abstract
The accurate and reliable monitoring of ventilation parameters is key to intelligent ventilation systems. In order to realize the visualization of airflow, it is essential to solve the airflow reconstruction problem using few sensors. In this study, a new concept called independent cut set that depends on the structure of the underlying graph is presented to determine the minimum number and location of sensors. We evaluated its effectiveness in a coal mine owned by Jinmei Corporation Limited (Jinmei Co., Ltd., Shanghai, China). Our results indicated that fewer than 30% of tunnels needed to have wind speed sensors set up to reconstruct the well-posed airflow of all the tunnels (>200 in some mines). The results showed that the algorithm was feasible. The reconstructed air volume of the ventilation network using this algorithm was the same as the actual air volume. The algorithm provides theoretical support for flow reconstruction.
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Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8950294 | PMC |
| http://dx.doi.org/10.3390/s22062096 | DOI Listing |
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