Abstract
Neurofuzzy approach to the estimation of the concentration of inflammable gas is proposed in this paper. The membership functions for the pur pose are made up of Fourier-transformed output signals of a semiconductor gas sensor (TGS 813). The resulting membership functions are used for training a neural nctwork which has the ability of learning fuzzy rules. Once the neural network is trained and verified to be pcrforminc, satisfactorily, it can be used to tune the membership functions automatically with the output signals of the sensor, and more precise estimation of the concentration can be expected, consequently. The proposed method is examined with the concentration-estimation of hydrogen and, as a result, good performance is achieved.
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