Electronic nose simulation tool centred on PSpice

Electronic noses consist of an array of non-selective gas sensors with a pa ttern recognition engine. The sensors and pattern recognition methods depen d on the specific application. The design process of electronic noses usual ly involves time-consuming measurements in a non-standard trial and error p rocess. This paper addresses the problem by using an electronic nose simula tion tool centred on PSpice. Using previously developed generic PSpice mode ls for the response of gas sensors, a four-element tin oxide sensor array w as simulated. The sensor model parameters were adjusted using calibrated re sponse data from ethanol, methane and their mixtures, detected with real ti n oxide sensors. To study the performance of the array, statistical error m odelling and PSpice simulations were used in a Monte Carlo analysis coupled with principal component analysis. The results show that this simulation s trategy is useful for analysing the effects of sampling errors, the changes in operation temperature, random errors and sensor drift. The importance o f these errors is discussed in terms of the array discrimination ability. W e conclude that this simulation strategy can help to systematise the design of electronic noses. (C) 2001 Elsevier Science B.V. All rights reserved.