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Three kinds of nozzles normally used in industrial production are numerically simulated, and the structure of nozzle with the best jetting performance out of the three nozzles is optimized. TheR90 nozzle displays the most optimal jetting properties, including the smooth transition of the nozzle’s inner surface. Simulation results of all sample nozzles in this study show that the helix nozzle ultimately displays the best jetting performance. Jetting velocity magnitude alongYandZcoordinates is not symmetrical for the helix nozzle. Compared to simply changing the jetting angle, revolving the jet issued from the helix nozzle creates a grinding wheel on the cleaning surface, which makes not only an impact effect but also a shearing action on the cleaning object. This particular shearing action improves the cleaning process overall and forms a wider, effective cleaning range, thus obtaining a broader jet width.

In this paper, a new 5-D chaotic system with hidden attractor was presented. The stability and equilibrium points set of the system were analyzed by the traditional dynamical analysis method. Meanwhile, several special phenomena were found in the system, such as chaos degradation, state transition, multiwing chaotic attractors, coexisting-attractors etc. verifying the application of the system in engineering, offset boosting control method is introduced and numerical simulation of the system is implemented. In addition, the complexity of Spectral Entropy (SE) and C 0 are analyzed. Finally, the new system was simulated by the digital signal processing (DSP) technology, and the results agree well with the numerical simulation result. Theoretical analysis and simulation results show that the system has complex dynamical characteristics and can be applied to secure communication and image encryption.

The study of hyperspectral imaging in tandem with spectral preprocessing and neural network techniques was conducted to realize Colla Corii Asini (CCA, E'jiao) adulteration discrimination. CCA was adulterated with pig skin gelatin (PSG) in the range of 5-95% (w/w) at 5% increments. Three methods were used to pretreat the original spectra, which are multiplicative scatter correction (MSC), Savitzky-Golay (SG) smoothing, and the combination of MSC and SG (MSC-SG). SPA was employed to select the characteristic wavelengths (CWs) to reduce the high dimension. Colour and texture features of CWs were extracted as input of prediction model. Two kinds of artificial neural network (ANN) with three spectral preprocessing methods were applied to establish the prediction models. The prediction model of generalized regression neural network (GRNN) in tandem with the MSC-SG preprocessed method presented satisfactory performance with the correct classification rate value of 92.5%. The results illustrated that the integration of preprocessing methods, hyperspectral imaging features, and ANN modeling had a great potential and feasibility for CCA adulteration discrimination.