Analysis of Hydrogen Gas Sensing Characteristics Based on a Grey Polynomial Differential Model (GPDM) Algorithm

The interesting hydrogen gas sensing characteristics, based on a field-effect transistor (FET)-based sensor, are studied and analyzed. In addition, a new grey algorithm is developed to reduce the computing complexity. From experimental results, the studied device exhibits good hydrogen performance for wide hydrogen concentration detection and widespread operation temperature. For practical applications, it is important to reduce the computational complexity and eliminate data redundancy. In this paper, a new grey polynomial differential model (GPDM) is developed to analyze hydrogen gas sensing properties. Based on the proposed model, the simulated data points are substantially decreased from 4000 points (the measured results) to 68 points (GPDM data). It is worth to note that, the simulated curve still retains the original features of experimental hydrogen transient response. The error rate between the simulated data and experimental results is only of 0.091%. Therefore, the reported GPDM presents the promise on the analysis of hydrogen gas sensing performance by reducing the undesired computing complexity and data redundancy.