基于纸喷雾离子化衍生质谱法快速检测PM2.5中的醌污染物

醌类化合物是PM2.5中的一类有害物质。本研究建立了纸喷雾离子化衍生质谱法快速测定PM2.5中的醌类污染物。通过衍生化反应在醌化合物中引入氨基，提高醌在纸喷雾中的离子化效率。随后对衍生化试剂种类、电压、喷雾溶剂种类等反应条件进行优化。在最优实验条件下，采用内标法定量分析1,4-苯醌、甲基对苯醌、1,4-萘醌和1,4-蒽醌，4种化合物均呈现较好的线性关系，其检出限分别为4.49、20.89、0.13、0.17 ng。利用该方法分析PM2.5实际样品中的萘醌和蒽醌，均获得了较好的定性和定量结果。     

往复活塞式压缩机活塞杆温度高故障分析及改造

针对2台2D40型空气压缩机在实际试机过程中,活塞杆温度过高,导致连锁报警,压缩机不能正常工作的问题进行了详细的故障原因分析;对压缩机技术性能参数进行介绍;对压缩机的损伤情况进行说明并找到改造方案,解决机组运行中活塞杆温度过高的问题,从而提高机组的运行效率,使机组运行安全、稳定。     

Frequency response data-based peak filter design applied to MIMO large-scale high-precision scan stage

A large-scale high-precision scan stage is important equipment in the industrial productions of micro-fabrication such as flat panel display (FPD) lithography systems. Designing controllers for multi-input multi-output (MIMO) systems is time-consuming and needs experience because of the interaction between each axis and many controller tuning parameters. The aim of this study is to develop a peak filter design method based on frequency response data to reduce repetitive disturbance. This data-based approach does not use the model and only uses the frequency response data of the controlled system and the disturbance spectrum calculated from the scanning error data (Contribution 1). The peak filter is designed by convex optimization and satisfies robust stability conditions for six-degree-of-freedom systems (Contribution 2). The control performance of the designed peak filter is experimentally demonstrated with an industrial MIMO large-scale high-precision scan stage in reducing the scanning error of the main stroke of the translation along the $x$-axis (Contribution 3).     

One-step to prepare high-performance gas diffusion layer (GDL) with three different functional layers for proton exchange membrane fuel cells (PEMFCs)

Gas diffusion layer (GDL) is one of the most important components of fuel cells. In order to improve the fuel cell performance, GDL has developed from single layer to dual layers, and then to multiple layers. However, dual or multi layers in GDL are usually prepared by layer-by-layer methods, which cost too much time, energy, and resources. In this work, we successfully developed a facile one-step method to prepare a GDL with three functional layers by utilizing the different sedimentation rates and filtration rates of short carbon fiber (CF) and carbon nanotube (CNT). The treatment temperature for this GDL is much lower than that of traditional method. The thickness of the GDL can be effectively controlled from as thin as 50 μm to more than 200 μm by simply adjusting the content of CF. The GDL with high flexibility is suitable to develop high performance flexible electronics. The fuel cell with the GDL has the maximum power density 1021 mW cm^?2, which shows 19% improvement comparing to the conventional one. Therefore, this work breaks the traditional concept that GDL for fuel cells only can be prepared by very complex and high-cost procedure.     

Analysis of pressure and heat distribution in a dilating or contracting filter chamber with two outlets using multivariate spectral quasilinearization method

The development of efficient filters is an essential part of industrial machinery design, specifically to increase the lifespan of a machine. In the filter chamber design considered in this study, the magnetic material is placed along the horizontal surface of the filter chamber. The inside of the filter chamber is layered with a porous material to restrict the outflow of unwanted particles. This study aims to investigate the flow, pressure, and heat distribution in a dilating or contracting filter chamber with two outlets driven by injection through a permeable surface. The proposed model of the fluid dynamics within the filter chamber follows the conservation equations in the form of partial differential equations. The model equations are further reduced to a steady case through Lie's symmetry group of transformation. They are then solved using a multivariate spectral-based quasilinearization method on the Chebyshev–Gauss–Lobatto nodes. Insights and analyses of the thermophysical parameters that drive optimal outflow during the filtration process are provided through the graphs of the numerical solutions of the differential equations. We find, among other results, that expansion of the filter chamber leads to an overall decrease in internal pressure and an increase in heat distribution inside the filter chamber. The results also show that shrinking the filter chamber increases the internal momentum inside the filter, which leads to more outflow of filtrates.     

Investigation of fabrication of gas diffusion substrate for proton exchange membrane fuel cells

The gas diffusion substrate (GDS) is essential in the proton exchange membrane fuel cells. Its fabrication techniques affect the performance significantly and are worthy of investigation. In this study, a manufacturing process of the GDS is proposed to understand the formation process of GDS and promote its structure and performance more pertinently. Different states during the preparation process, raw carbon paper, pre-curing, curing, carbonation, and graphitization, are characterized and measured. Experimental and numerical methods are employed to determine the relationships between microstructure, transport, and mechanical performance variation with the fabricating processes. The results show that its porosity, average pore size, and effective diffusivity decrease first and increase after curing. These parameters after graphitization are lower than that of the carbon paper (CP). The electrical resistivity increases dramatically while pre-curing and decreases gradually after curing, carbonation, and graphitization, and it is much reduced after graphitization. Moreover, mechanical measurement results show that both the picks of tensile strength and flexural modulus occur after curing. Its tensile strength shows little change after graphitization compared to the initial paper's. In contrast, the flexural modulus is improved significantly.     

Finite-time adaptive fuzzy control for a class of output constrained nonlinear systems with dead-zone

The article investigates the finite-time adaptive fuzzy control for a class of nonlinear systems with output constraint and input dead-zone. First, by skillfully combining the barrier Lyapunov function, backstepping design method, and finite-time control theory, a novel adaptive state-feedback tracking controller is constructed, and the output constraint of the nonlinear system is not violated. Second, the fuzzy logic system is used to approximate unknown function in the nonlinear system. Third, the finite-time command filter is introduced to avoid the problem of “complexity explosion” caused by repeated differentiations of the virtual control signal in conventional backstepping control schemes. Meanwhile, a new saturation function is added in the compensating signal for filter error to improve control accuracy. Finally, based on Lyapunov stability analysis, all the signals of the closed-loop are proved to be semi-globally uniformly ultimately bounded, and the tracking error converges to a small neighborhood region of the origin in a finite time. A simulation example is presented to demonstrate the effectiveness for the proposed control scheme.     

Influence of pulse-jet cleaning pressure on performance of compact dust collector with pleated filter operated in clean-on-time mode

To operate a bag filter continuously, pulse-jet cleaning of dust particles from the filter medium is commonly required, and the pulse-jet pressure significantly affects the filter performance. In this study, the accumulation structure of residual dust particles inside and on the surface of a filter medium at different pulse-jet pressures was investigated by constructing a simple model, and the influence of the dust structure on the filter performance was clarified. Using a simple model, we determined the effective ratio of filtration area β, which represents the ratio of the filterable area to the total filtration area, the true resistance coefficient due to the primary dust layer ζ_p’ thinly deposited on the filter surface, and the true resistance coefficient inside the filter media itself ζ_f’_. The effective ratio of filtration area β decreased with operation time for all pulse-jet pressures; however, it maintained a high value when the pulse-jet pressure was high. The validity of β analyzed by the model was verified using two different methods, and the results showed good agreement, indicating that the model is effective in identifying real conditions. The true resistance coefficient due to the primary dust layer ζ_p’ decreased as the pulse-jet pressure increased; however, the true resistance coefficient inside the filter media itself ζ_f’ was the highest at 0.5 MPa. In addition, the dust collection efficiency was different at each pulse-jet pressure, which was considered to be caused by the difference in the dust particle accumulation structure.     

A Fusion Kalman Filter and UFIR Estimator Using the Influence Function Method

In this paper, the Kalman filter (KF) and the unbiased finite impulse response (UFIR) filter are fused in the discrete-time state-space to improve robustness against uncertainties. To avoid the problem where fusion filters may give up some advantages of UFIR filters by fusing based on noise statistics, we attempt to find a way to fuse without using noise statistics. The fusion filtering algorithm is derived using the influence function that provides a quantified measure for disturbances on the resulting filtering outputs and is termed as an influence finite impulse response (IFIR) filter. The main advantage of the proposed method is that the noise statistics of process noise and measurement noise are no longer required in the fusion process, showing that a critical feature of the UFIR filter is inherited. One numerical example and a practice-oriented case are given to illustrate the effectiveness of the proposed method. It is shown that the IFIR filter has adaptive performance and can automatically switch from the Kalman estimate to the UFIR estimates according to operating conditions. Moreover, the proposed method can reduce the effects of optimal horizon length on the UFIR estimate and can give the state estimates of best accuracy among all the compared methods.      

Long-term performance analysis of chemical filters in clean rooms based on a prediction model

Chemical filters are the most important devices for removing gas-phase pollutants in clean rooms. However, the testing concentration of chemical filters is too high for reflecting their performance in a real clean room environment. This study tested the adsorption performance of chemical filters in the two most commonly used shapes at different concentrations. Then, the Langmuir equation and Wheeler-Jonas kinetic equation were combined to establish an adsorption performance prediction model of chemical filters under actual conditions. The predicted values of the model were in good agreement with the experimental results, which indicated the high accuracy of the prediction model. The model does not need to test the microscopic parameters of the adsorbent and can maintain high accuracy at low concentrations. A fast method for calculating the service life of chemical filters was also presented. Based on this model, the total cost of using a chemical filter with a high carbon content in microelectronic clean rooms could be decreased by 45% due to decreasing the number of filter replacements over 3 months. So a chemical filter with a high carbon content should be preferred over a filter with low resistance in microelectronic clean rooms.