TY - GEN
T1 - A least squares approach for learning gas distribution maps from a set of integral gas concentration measurements obtained with a TDLAS sensor
AU - Trincavelli, Marco
AU - Bennetts, Victor Hernandez
AU - Lilienthal, Achim J.
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84873973113&partnerID=8YFLogxK
U2 - 10.1109/ICSENS.2012.6411118
DO - 10.1109/ICSENS.2012.6411118
M3 - Conference contribution
AN - SCOPUS:84873973113
SN - 9781457717659
T3 - Proceedings of IEEE Sensors
BT - IEEE SENSORS 2012 - Proceedings
T2 - 11th IEEE SENSORS 2012 Conference
Y2 - 28 October 2012 through 31 October 2012
ER -