Department of System Engineering and Automation, University of Málaga, Campus de Teatinos, 29071 Málaga, Spain.
Sensors (Basel). 2012 Oct 11;12(10):13664-80. doi: 10.3390/s121013664.
Metal Oxide Semiconductor (MOX) gas transducers are one of the preferable technologies to build electronic noses because of their high sensitivity and low price. In this paper we present an approach to overcome to a certain extent one of their major disadvantages: their slow recovery time (tens of seconds), which limits their suitability to applications where the sensor is exposed to rapid changes of the gas concentration. Our proposal consists of exploiting a double first-order model of the MOX-based sensor from which a steady-state output is anticipated in real time given measurements of the transient state signal. This approach assumes that the nature of the volatile is known and requires a precalibration of the system time constants for each substance, an issue that is also described in the paper. The applicability of the proposed approach is validated with several experiments in real, uncontrolled scenarios with a mobile robot bearing an e-nose.
金属氧化物半导体（MOX）气体传感器是构建电子鼻的首选技术之一，因为它们具有高灵敏度和低成本。在本文中，我们提出了一种方法，可以在一定程度上克服它们的主要缺点之一：恢复时间慢（数十秒），这限制了它们在传感器暴露于气体浓度快速变化的应用中的适用性。我们的建议包括利用基于 MOX 的传感器的双一阶模型，该模型可以根据瞬态信号的测量实时预测稳态输出。该方法假设挥发性物质的性质是已知的，并且需要针对每种物质对系统时间常数进行预校准，这也是本文中描述的问题。通过在带有电子鼻的移动机器人上进行的几个实际、非控制场景中的实验验证了所提出方法的适用性。
