Multi-sensor multi-spectrum pattern recognition and its application in chemical process test

The main obstacle in developing chemical sensor is that most of chemical sensing materials lack satisfactory sensitivity and selectivity to the chemical objects. In recent year, a great amount of efforts in solving the problem have been made, for instance, by composing sensing array with different materials or pattern recognition based on artificial neural networks. These efforts, however, are quite limited due to the fact that the excitation signal on single or fixed frequency is not suitable for sensing elements with different optical characteristics. In this paper, a new pattern recognition method based on multi-sensor multi-spectrum is proposed. The multi-sensor is composed of the sensing array made by non-selective sensing material and excited by a continuous spectrum. As the continuous spectrum covers a relatively wide frequency scope, the sensor array can describe different optical characteristics and create abundant sensing information. The adaptive sampling procedure of the spectrum and data processing algorithms are also given for the universal pattern recognition. The experiment results show that the method proposed in this paper can reduce evidently the requirements on sensitivity and selectivity of the sensing materials and is thus helpful to the practical realization of the chemical sensor.