Leak Detection and Localization in Multi-Grid Space Using Improved Gaussian Plume Model

泄漏 网格 正确性 计算机科学 高斯分布 羽流 生物系统 扩散 算法 环境科学 模拟 化学 数学 物理 环境工程 热力学 计算化学 生物 几何学
作者
Daquan Li,Gaigai Liu,Zhaoyong Mao
出处
期刊:Sensors [Multidisciplinary Digital Publishing Institute]
卷期号:23 (13): 6209-6209 被引量:5
标识
DOI:10.3390/s23136209
摘要

Leak detection and localization of liquid or gas is of great significance to avoid potential danger and reduce the waste of resources. Leak detection and localization methods are varied and uniquely suited to specific application scenarios. The existing methods are primarily applied to conventional pressurized pipelines and open areas, and there are few methods suitable for multi-grid spaces. In this paper, a gas diffusion model applied to multi-grid space is constructed, and a method for leak detection and localization using the concentration gradient of characteristic gas is proposed according to the prediction behavior. The Gaussian plume model is selected due to its advantages of simplicity and the interpretation of gas diffusion behavior is closer to reality; the expression of the improved model is also obtained. To verify the correctness of the model and the applicability of the localization method, taking the coolant leakage in the circuit system as an example, three experiments with different source strengths were repeated. The fitting correlation coefficients between the gas concentration data of the three experiments and the model are 0.995, 0.997 and 0.997, respectively. The experimental results show that the model has a strong correlation with the real plume behavior, and it is reasonable to use the gas concentration gradient for the localization of the leak source. This study provides a reference for future research on the leak detection and localization of gas- or liquid-containing volatile substances in a complex multi-grid space.
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