A Study on Predicting the Deviation of Jet Trajectory Falling Point under the Influence of Random Wind

TL;DR

This paper introduces a system and method to predict how random wind affects the accuracy of sprinkler fire extinguishing systems.

Contribution

A new random wind acquisition system and a Random Forest-based prediction method for jet trajectory falling points are proposed.

Findings

The proposed method reduced the x-direction error from 2.11 m to 1.53 m at 50 m.

The total mean absolute error (MAE) was reduced from 31.3 to 23.5.

The method demonstrated feasibility in predicting falling points under random wind at different distances.

Abstract

As one of the main external factors affecting the fire extinguishing accuracy of sprinkler systems, it is necessary to analyze and study random wind. However, in practical applications, there is little research on the impact of random wind on sprinkler fire extinguishing points. To address this issue, a new random wind acquisition system was constructed in this paper, and a method for predicting jet trajectory falling points in Random Forest (RF) under the influence of random wind was proposed, and compared with the commonly used prediction model Support Vector Machine (SVM). The method in this article reduces the error in the x direction of the 50 m prediction result from 2.11 m to 1.53 m, the error in the y direction from 0.64 m to 0.6 m, and the total mean absolute error (MAE) from 31.3 to 23.5. Simultaneously, predict the falling points of jet trajectory at different distances under the influence of random wind, to demonstrate the feasibility of the proposed method in practical applications. The experimental results show that the system and method proposed in this article can effectively improve the influence of random wind on the falling points of a jet trajectory. In summary, the image acquisition system and error prediction method proposed in this article have many potential applications in fire extinguishing.

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