An Application of the Gaussian Plume Model to Localization of an Indoor Gas Source with a Mobile Robot

Abstract

The source localization of gas leaks is important to avoid any potential danger to the surroundings or the probable waste of resources. Currently there are several localization methods using robotic systems that try to find the origin of a gas plume. Many of these methods require wind velocity information involving the use of commercial anemometric systems which are extremely expensive compared to metal oxide gas sensors. This article proposes the validation of the Gaussian plume model inside an empty room and its application to localize the source of a gas plume without employing anemometric sensors, exclusively using concentration data. The model was selected due to its simplicity and since it easily admits variants closer to reality, explaining the behavior of pollutants transported by the wind. An artificial gas source was generated by a conventional fan and liquid ethanol as contaminant. We found that the physical fan, far from making the model impossible to implement, enriched the information and added realism. The use of a robotic system capable of autonomously mapping the room concentration distribution is described. The results showed that the Gaussian plume model is applicable to localize our experimental gas source. An estimated position of the source with a deviation of 14 cm (6.1%) was obtained.

Application of an Array of Metal-Oxide Semiconductor Gas Sensors in an Assistant Personal Robot for Early Gas Leak Detection

“…The main reason for this phenomenon was the vertical distance between the gas source (located at ground level) and the gas sensor (55 cm above the ground), combined with the air currents induced by the HVAC system, causing the plume to be pushed away from the source. This was already observed by Sánchez-Sosa et al [30] and is later confirmed by results obtained with the HVAC system turned off.…”

“…The novelty of this contribution lies in the number of MOX sensors used, on the low concentrations of the target gas, on the presence of chemical interferences, and on the dimensions (15 m × 40 m) and complexity of the testing environment. These conditions represent an improvement over similar validations performed in simulated scenarios [13] or in smaller areas [19] containing a single gas source [26] and artificially induced unidirectional airflows [30]. The experimental arena is one floor of a university building, in which a hypothetic gas leak can potentially spread very fast and affect many people.…”

Application of a Small Unmanned Aerial System to Measure Ammonia Emissions from a Pilot Amine-CO2 Capture System

“…The model was chosen due to its proven performance over small distances. In other words, this model has been used on small scales on many occasions and successfully modeled the dispersion of gas molecules [36][37][38]. The model was effectively applied to NH 3 (g), as the measurements of this pollutant were completed under stable meteorological conditions for a short distance in less than 1 h, which is much shorter than its atmospheric lifetime, τ NH 3 (g) = 1 day [28,39].…”

Effective Exploration Behavior for Chemical-Sensing Robots

“…This function is an approximation for a point source of chemical effluent [35]. Other choices, for example, a Gaussian plume model [36], could also be used. Figure 3 (left) shows a surface plot of the fixed time function with these parameters.…”