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Both the long-life and multi-mode versions of LIPS-200 ion thruster are under investigation in LIP (Lanzhou Institute of Physics). To confirm the feasible ranges of the beam current and accel (abbreviation for accelaration) grid potential to apply to the thruster, the wide-range beam perveance (the state of beam focus) and saddle point potential (the lowest potential along beamlet centerline) characteristics of LIPS-200 are studied with a test-verified PIC-MCC (Particle in Cell-Monte Carlo Collisions) model. These characteristics are investigated with both the initial and the eroded states of the accel grid aperture diameter. The results show that the feasible ranges of these parameters with respect to perveance/crossover (overfocused) limit extend as the operating time accumulates, while the feasible range of accel grid potential narrows due to a reduced EBSF (electron backstreaming failure) margin. The feasible ranges determined by the initial condition are: (i) the beam current up to 0.981 A, and (ii) the accel grid potential up to −85 V. A 23% enlargement of the aperture diameter would bring up to 48 V of EBSF margin loss.

Facial expression recognition is a hot topic in the field of computer vision. The related research results show high application value in many fields, such as human-computer interaction, intelligent emotional robot, fatigue driving detection, medical health, safety prevention and control, teaching evaluation and so on. However, the huge difference within the expression class still has a prominent impact on the expression recognition, and it is difficult to solve this problem by single feature and traditional feature fusion methods. Therefore, this paper uses neural network and feature fusion strategy to further characterize and classify the constructed features. Experiments show that this method can effectively overcome the interference caused by the differences within the expression class, and achieve ideal expression recognition results.

Aiming at the problems of various sensors, complex recognition algorithm poor implement ability and real-time performance in current human activity state recognition methods, a human activity monitor based on single three-axis acceleration sensor is designed. By collecting acceleration data of human waist, using sliding time window method to extract time domain features, four active states are identified: long-term violent active state. Long-term static state, fall state and normal active state. The technical development and the existing difficulties and problems are discussed for future related research.

Accelerator grid structural and electron backstreaming failures are the most important factors affecting the ion thruster's lifetime. During the thruster's operation, Charge Exchange Xenon (CEX) ions are generated from collisions between plasma and neutral atoms. Those CEX ions grid's barrel and wall frequently, which cause the failures of the grid system. In order to validate whether the 20 cm Lanzhou Ion Propulsion System (LIPS-200) satisfies China's communication satellite platform's application requirement for North-South Station Keeping (NSSK), this study analyzed the measured depth of the pit/groove on the accelerator grid's wall and aperture diameter's variation and estimated the operating lifetime of the ion thruster. Different from the previous method, in this paper, the experimental results after the 5500 h of accumulated operation of the LIPS-200 ion thruster are presented firstly. Then, based on these results, theoretical analysis and numerical calculations were firstly performed to predict the on-orbit lifetime of LIPS-200. The results obtained were more accurate to calculate the reliability and analyze the failure modes of the ion thruster. The results indicated that the predicted lifetime of LIPS-200's was about 13218.1 h which could satisfy the required lifetime requirement of 11000 h very well.