基于延迟模式相似性度量的电子鼻气体识别

Muhammad Hassan, A. Bermak, Amine Ait Si Ali, A. Amira
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引用次数: 1

摘要

最近,为电子鼻系统开发了实现友好的生物启发编码方案,以识别不同的气体。在这些方案中,使用对数时域编码技术将电子鼻中传感器阵列的响应向量转换为延迟模式。对于每个目标气体,这些方案假定一个唯一的延迟时间序列,称为秩顺序。然而,较差的可重复性和传感器漂移限制了这些方案的性能。在本文中,我们使用传感器阵列的延迟模式之间的角分离进行气体识别。开发了一种包含一系列商用气体传感器和射频模块的电子鼻系统,并在四种气体的实验室环境中进行了表征。实验数据用于比较我们的编码方案与现有的仿生编码方案和常用的模式识别算法的性能。
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Gas identification in electronic nose by using similarity measure between latency patterns
Recently, implementation friendly bio-inspired coding schemes have been developed for an electronic nose system to recognise different gases. In these schemes, a logarithmic time-domain encoding technique is used to covert the response vector of the sensor array in an electronic nose into a latency pattern. These schemes assume a unique temporal sequence of latencies, referred to as a rank order, for each target gas. However, poor repeatability and sensor drift limit the performance of these schemes. In this paper, we use angular separation between the latency patterns of the sensor array for gas identification. An electronic nose system containing an array of commercially available gas sensors and a radio frequency module is developed and characterized in the laboratory environment with four gases. Experimental data is used to compare the performance of our coding scheme with existing bio-inspired coding schemes and commonly used pattern recognition algorithms.
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