Marco Trincavelli, Victor Hernandez Bennetts and Achim J. Lilienthal
A Least Squares approach for learning gas distribution maps from a set of integral gas concentration measurements obtained with a TDLAS sensor
Proceedings of the IEEE Sensors Conference, October 28-31, 2012, Taipei, Taiwan.
Abstract: Applications related to industrial plant surveillance and environmental monitoring often require the creation of gas distribution maps (GDM). In this paper an approach for creating a gas distribution map using a Tunable Diode Laser Absorption Spectroscopy (TDLAS) sensor and a laser range scanner mounted on a pan tilt unit is presented. The TDLAS sensor can remotely sense the target gas, in this case methane, requiring novel GDM algorithms compared to the ones developed for traditional in-situ chemical sensors. The presented setup makes it possible to create a 3D model of the environment and to calculate the path travelled by the TDLAS beam. The knowledge of the beam path is of crucial importance since a TDLAS sensor provides an integral measurement of the gas concentration over that path. An efficient GDM algorithm based on a quadratic programming formulation is proposed. The approach is tested in an indoor scenario where transparent bottles filled with methane are successfully localized.
Keywords:Absorption, Gas lasers, Laser beams, Measurement by laser beam, Noise, Noise measurement, Robot sensing systems
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@INPROCEEDINGS{Trincavelli_etal:IEEESensors12:2012,
  AUTHOR = {Trincavelli, Marco and Hernandez Bennetts, Victor and Lilienthal, Achim},
  TITLE = {A Least Squares approach for learning gas distribution maps from a set of integral gas concentration measurements obtained with a TDLAS sensor},
  BOOLTITLE = {Sensors, 2012 IEEE},
  VOLUME = {},
  YEAR = {2012},
  DATE = {October 28-31},
  ADRESS = {Taipei, Taiwan},
  PAGES = {1-4}
  DOI = {10.1109/ICSENS.2012.6411118}
}