A new method was developed based on the electron beam vacuum dispersion（EBVD） technology to prepare the PTFE polymer coating of the new polymer quartz piezoelectric crystal sensor for testing liquor products. The new method was applied in the new EBVD equipment which we designed. A real-time system monitoring the polymer coating＇s thickness was designed for the new EBVD equipment according to the quartz crystal microbalance（QCM） principle, playing an important role in preparing stable and uniform PTFE polymer coatings of the same thickness. 30 pieces of PTFE polymer coatings on the surface of the quartz crystal basis were prepared with the PTFE polymer ultrafine powder（purity ≥ 99.99%）as the starting material. We obtained 30 pieces of new PTFE polymer sensors. By using scanning electron microscopy（SEM）, the structure of the PTFE polymer coating＇s column clusters was studied. One sample from the 30 pieces of new PTFE polymer sensors was analysed by SEM in four scales, i.e., 400×, 1000×, 10000×, and 25000×. It was shown that under the condition of high bias voltage and low bias current, uniformly PTFE polymer coating could be achieved, which indicates that the new EBVD equipment is suitable for mass production of stable and uniform polymer coating.
We present a new pattern recognition system based on moving average and linear discriminant analysis （LDA）, which can be used to process the original signal of the new polymer quartz piezoelectric crystal air-sensitive sensor system we designed, called the new e-nose. Using the new e-nose, we obtain the template datum of Chinese spirits via a new pattern recognition system. To verify the effectiveness of the new pattern recognition system, we select three kinds of Chinese spirits to test, our results confirm that the new pattern recognition system can perfectly identify and distinguish between the Chinese spirits.
This paper presents a new pattern recognition system for Chinese spirit identification by using the polymer quartz piezoelectric crystal sensor based e-nose. The sensors are designed based on quartz crystal microbalance（QCM） principle,and they could capture different vibration frequency signal values for Chinese spirit identification. For each sensor in an8-channel sensor array, seven characteristic values of the original vibration frequency signal values, i.e., average value（A）,root-mean-square value（RMS）, shape factor value（S_f）, crest factor value（C_f）, impulse factor value（I_f）, clearance factor value（CL_f）, kurtosis factor value（K_v） are first extracted. Then the dimension of the characteristic values is reduced by the principle components analysis（PCA） method. Finally the back propagation（BP） neutral network algorithm is used to recognize Chinese spirits. The experimental results show that the recognition rate of six kinds of Chinese spirits is 93.33% and our proposed new pattern recognition system can identify Chinese spirits effectively.
