Sự suy giảm của màng nhựa acrylic nhũ tương primal AC-261 trong môi trường thời tiết nhân tạo

The degradation of the Primal AC-261 water-based acrylic film (AC-261) in the artifical weathering environment has been studied by fourier-transform infrared (FTIR) and ultraviolet - visible (UV-Vis) spectroscopy, microscope and weight loss analysis. The IR and UV-Vis analysis showed that the level of C-H (alkanes) and C-O- (ester) stretchings decreased while O-H, C=O and C=C (alkene) stretchings increased in the artifical weathering testing process by a QUV weathering chamber equipped with UVB-313 fluorescent lamps and operated under wet-cycle conditions of 8 h UV irradiation at 60 °C, followed by 4 h of dark water condensation at 50 °C. After 96 cycles (1152 hours), the film surface had many black spots and weight loss of the film was 18 %

Nghiên cứu ảnh hưởng của xử lý plasma đến độ bám dính của lớp phủ khâu mạch quang trên nền polypropylen. Phần 1. Nghiên cứu ảnh hưởng của xử lý plasma không khí đến tính chất bề mặt polypropylen.

In this work, polypropylene (PP) was treated by air plasma to improve its adhesion properties. The influence of plasma treatment time was studied. As can be showed from results of static contact angle, the air plasma treatment improved significantly hydrophilic property of PP surface - the contact angle was reduced from 109 to 56o, respectively, before and after 3 minutes plasma treatment. In addition, Scanning Electron Microscope (SEM) images showed that after plasma treatment, the morphology of polymer surface saw rougher than before. The results of Fourier Transformed Infrared Spectroscopy (FT-IR) also presented that newly created hydrophilic functional groups (C=O, O-H) on the polypropylene surface caused by plasma treatment. As a result, the lap-shear strengths of PP after plasma treatment were substantially improved. As can be conclude from the results of this study, the suitable plasma treatment time for PP was 3 minutes

Identification of A Nonlinear Model of Switched Reluctance Motor Which Considers the Effects of Mutual Inductance and Magnetic Saturation

The paper presents a full nonlinear model for switched reluctance motor (SRM) based on artificial neural networks. The proposed neural network model consists of two different models, the forward one and the inverse one. The purpose of the forward model represents relationship between the flux linkage and torque as a functional dependence on the current stator and the position rotor. The inverse model is used to estimate current stator and flux linkage as a functional dependence on torque and rotor position. The tested SRM model is built on the basis of software simmechanic. The used neural networks is a multi-layered network and is trained with a feedforward algorithm. The nonlinear model proposed in this paper can be used to synthesize controllers for SRM in the following applications

Backstepping Control for Combination Model of Switched Reluctance Motor

Switched Reluctance Motor (SRM) has many advantages with very strong nonlinearity, hence it is difficult to control. The paper presents a method to design a nonlinear controller for SRM based on backstepping nonlinear control technique. This controller is first applied to SRM which its mathematical model is a combination of both the commutator and the motor in the same model. The combination model of SRM contributes to reduce the influence of nonlinearity due to the switching lock, increasing the accuracy in controlling this motor. The stability of the closed control loop was analyzed based on the Lyapunov stability standard. The simulation results performed on Matlab/Simulink confirmed the accuracy of the combination model and the quality of the backstepping control system