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

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.