Optimising of the sensing chamber of an array of a volatile detection system

A fluid dynamic analysis was performed to optimise the positioning of sensor elements in a coated quartz crystal microbalance (QCM) based volatile detection system. The computational fluid dynamic (CFD) code used solves the Navier-Stokes equations statically and dynamically in 2D, discretised by finite elements. In the original sensor chamber, the sensor elements were positioned in a staggered pattern and at 90° to the incoming flow. The numerical analysis shows that, with the exception of the front face of the first sensor, only 45% of the flow passed over the sensors. It is shown that the response of sensor elements is strongly dependent on the sensor position. An optimised sensor chamber design was developed where the sensors are at 0° to the flow direction and a baffle plate diffuses the flow evenly over the sensor elements. The sensors are shown to receive the same flow and respond identically irrespective of position.

[1]  Fredrik Winquist,et al.  Drift counteraction in odour recognition applications: lifelong calibration method , 1997 .

[2]  Liu Junhua,et al.  Drift reduction of gas sensor by wavelet and principal component analysis , 2003 .

[3]  A. Guadarrama,et al.  Discrimination of wine aroma using an array of conducting polymer sensors in conjunction with solid-phase micro-extraction (SPME) technique , 2001 .

[4]  J. Slater,et al.  Interpreting signals from an array of non-specific piezoelectric chemical sensors , 1996 .

[5]  Claudio Domenici,et al.  Fluid dynamic simulation of a measurement chamber for electronic noses , 2002 .

[6]  N. Freeman,et al.  Response kinetics of polymer-coated bulk acoustic wave devices on exposure to gases and vapours , 1994 .

[7]  G. Sauerbrey,et al.  Use of quartz vibration for weighing thin films on a microbalance , 1959 .

[8]  G. Sauerbrey Verwendung von Schwingquarzen zur Wägung dünner Schichten und zur Mikrowägung , 1959 .

[9]  K. R. Kashwan,et al.  Tea quality prediction using a tin oxide-based electronic nose: an artificial intelligence approach , 2003 .

[10]  W. T. O'Hare,et al.  Radial basis neural network for the classification of fresh edible oils using an electronic nose , 2003 .

[11]  D. James,et al.  Gas-phase pre-concentration for a quartz crystal microbalance based electronic nose , 2003 .

[12]  P. Schulze Lammers,et al.  Online measurement of odorous gases close to the odour threshold with a QMB sensor system with an integrated preconcentration unit , 2003 .

[13]  Michele Penza,et al.  Application of principal component analysis and artificial neural networks to recognize the individual VOCs of methanol/2-propanol in a binary mixture by SAW multi-sensor array , 2003 .

[14]  Edward T. Zellers,et al.  Vapor recognition with an integrated array of polymer-coated flexural plate wave sensors , 2000 .

[15]  M. K. Andrews,et al.  Conducting polymer sensors for monitoring aromatic hydrocarbons using an electronic nose , 2002 .