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A gas concentration estimation method based on multivariate relevance vector machine using MOS gas sensor arrays

机译:基于多元相关向量机的MOS气体传感器阵列气体浓度估算方法

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摘要

Machine Olfaction is a bionic detection technique that adopts electronic device to simulate biological olfactory system. As an information acquisition device, MOS gas sensor array is an important component of machine olfactory system. In this paper, a novel gas concentration estimation method based on multivariate relevance vector machine (MVRVM) is proposed for mixed gas detection by using MOS gas sensor array. The proposed method utilizes the excellent multivariate regression analysis performance of MVRVM to estimate any one analyte concentration in the mixed gas. To demonstrate the performance of proposed gas concentration estimation method, a machine olfactory system is designed and implemented. Gas concentration experiments with methane and carbon monoxide gas mixture as the research object were performed in the above machine olfactory system. Experimental results show that the proposed method can provide a good solution for mixed gas concentration estimation in the aspects of estimated accuracy and computational complexity.
机译:机器嗅觉是一种仿生检测技术,它采用电子设备模拟生物嗅觉系统。 MOS气体传感器阵列作为一种信息采集设备,是机器嗅觉系统的重要组成部分。提出了一种基于多元相关向量机(MVRVM)的气体浓度估算方法,该方法用于利用MOS气体传感器阵列进行混合气体检测。所提出的方法利用MVRVM出色的多元回归分析性能来估计混合气体中任何一种分析物的浓度。为了证明所提出的气体浓度估算方法的性能,设计并实现了一种机器嗅觉系统。在上述机器嗅觉系统中,以甲烷和一氧化碳混合气为研究对象进行了气体浓度实验。实验结果表明,该方法在估计精度和计算复杂度方面可以为混合气体浓度估计提供良好的解决方案。

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