In this paper, the long-term reliability of swash plate type hydraulic pump is studied by prognostics method. For the purpose, the pumping power of hydraulic pump is measured for 00 cycles and the performance after 00 cycles is estimated using the particle filter method. To verify the predicted 00 cycle's performance, the actual test results are compared with the estimated result and the trend of estimation is well matched with actual test results. The long-term reliability evaluation using the prognostics method performed in this study shows the feasibility that can be utilized in development phase of tracked vehicle to improve the quality of initial products.

For several years, keyboard and mouse have been used as the main interacting devices between users and computer games, but they are becoming outdated. Gesture-based human-computer interaction systems are becoming more popular owing to the emergence of virtual reality and augmented reality technologies. Therefore research on these systems has attracted a significant attention. The researches focus on designing the interactive interfaces between users and computers. Human-computer interaction is an important factor in computer games because it affects not only the experience of the users, but also the design of the entire game. In this research, we develop an particle filter-based face tracking method using color distributions as features, for the purpose of applying to gesture-based human-computer interaction systems for computer games. The experimental results proved the efficiency of particle filter and color features in face tracking, showing its potential in designing human-computer interactive games.

PURPOSES: The nonlinear model of fatigue cracking is typically used for determining the maintenance period. However, this requires that the model parameters be known. In this study, the particle filter (PF) method was used to determine various statistical parameters such as the mean and standard deviation values for the nonlinear model of fatigue cracking. METHODS: The PF method was used to determine various statistical parameters for the nonlinear model of fatigue cracking, such as the mean and standard deviation. RESULTS : On comparing the values obtained using the PF method and the least square (LS) method, it was found that PF method was suitable for determining the statistical parameters to be used in the nonlinear model of fatigue cracking. CONCLUSIONS : The values obtained using the PF method were as accurate as those obtained using the LS method. Furthermore, reliability design can be applied because the statistical parameters of mean and standard deviation can be obtained through the PF method.

In this study, the porous ceramic filter was developed to be able to remove both dust and hazardous gas contained in fuel gas at high temperature. The porous ceramic filters were fabricated and used as a catalyst support. And the effects have been investigated such as the mean particle size, organic content and addition of foaming agent on the porosity, compressive strength and pressure drop of ceramic filters. With the increase of mean powder size and the organic content for the cordierite filter, the porosity was increased, but the compressive strength and pressure drop were decreased. From the results of the research, the optimum condition for the fabrication of ceramic filters could be acquired and they had the porosity of 58%, the compressive strength of 13.4 MPa and the pressure drop of 250 Pa. It was expected that this ceramic filter was able to be applied to the glass melting furnace, combustor, and dust/toxic gas removal filter.

The purpose of this work is to develop a new type of particle collection filter using electrical discharge technology. The new filter must be high efficiency and applicable to air conditioner to use for household, so we suggested the new type filter. The new type filter has a distinctive feature except characteristic of ESP, a thickness of collecting electrodes is thicker than that of existing type ESP. When particles come into the filter, the particles will collide with side surfaces of the collecting electrodes. At the same time of particle collision with side surface, the particles are charged by the collision and collected by electrical force. Therefore, we called this type "Ion Impactor". We optimized condition of thickness of collecting electrodes and applied voltage using six sigma method because thickness of collecting electrodes and applied voltage are very important to improve the collection efficiency. We analyzed distribution of electric field line, the electric field lines were uniformly distributed on the side surface of the collecting electrodes. From this analysis, we can see the improvement of the particle collection efficiency. We made the ion impactor type filter on a large scale to equip to the air conditioner, and measured the particle collection efficiency. For the 0.1∼0.2㎛ range particle, the collection efficiency was higher than that of existing type ESP by 30%. The collection efficiency of the 0.3∼0.4㎛ range particle was higher by 12%.

Polluting gases emitted from industrial sites take compound forms consisting of gaseous and particulate phases. Localization of PTFE membrane filters has thus been initiated to remove particulate materials and mercury, which is a heavy and hazardous metallic element. More specifically, a PTFE membrane filter was fabricated by thermal laminating technology to vary porosity on the filter surface for removal of particulate materials thereon. Optimized equi-biaxial stretching ratio control enables minimization of large-size pore formation with an average pore size of 0.58 μm and improved air permeability of 8.03 cm3/cm2/sec. Various adsorbents were tested for removal of mercury vapor by surface treatment of the PTFE membrane filter. The filter’s surface was further altered using functional amine group compounds: one composed of silane coupling agent (APTMS) was found suitable as a mercury adsorbent. When ACF with a large surface area was used as support material, mercury removal efficiency increased threefold to 0.162 mg/g-ACF. Furthermore, the developed PTFE membrane filter was tested in its capacity of differential pressure and filtering efficiency using a pilot scale particulate removal unit. Stable and consistent differential pressure was maintained during long-term operation and less frequent periods of filter shutdown due to pores filling with 99.96% of particulate removal efficiency, which was more than satisfactory filtration efficiency.

For natural human-robot interaction, we need to know location and shape of facial feature in real environment. In order to track facial feature robustly, we can use the method combining particle filter and active appearance model. However, processing speed of this method is too slow. In this paper, we propose two ideas to improve efficiency of this method. The first idea is changing the number of particles situationally. And the second idea is switching the prediction model situationally. Experimental results is presented to show that the proposed method is about three times faster than the method combining particle filter and active appearance model, whereas the performance of the proposed method is maintained.

Recently, simultaneous localization and mapping (SLAM) approaches employing Rao-Blackwellized particle filter (RBPF) have shown good results. However, due to the usage of the accurate sensors, distinct particles which compensate one another are attenuated as the RBPF-SLAM continues. To avoid this particle depletion, we propose the strategic games to assign the particle’s payoff which replaces the importance weight in the current RBPF-SLAM framework. From simulation works, we show that RBPF-SLAM with the strategic games is inconsistent in the pessimistic way, which is different from the existing optimistic RBPF-SLAM. In addition, first, the estimation errors with applying the strategic games are much less than those of the standard RBPF-SLAM, and second, the particle depletion is alleviated.

Recently, simultaneous localization and mapping (SLAM) approaches employing Rao-Blackwellized particle filter (RBPF) have shown good results. However, no research is conducted to analyze the result representation of SLAM using RBPF (RBPF-SLAM) when particle diversity is preserved. After finishing the particle filtering, the results such as a map and a path are stored in the separate particles. Thus, we propose several result representations and provide the analysis of the representations. For the analysis, estimation errors and their variances, and consistency of RBPF-SLAM are dealt in this study. According to the simulation results, combining data of each particle provides the better result with high probability than using just data of a particle such as the highest weighted particle representation.

The Intelligent Space(ISpace) provides challenging research fields for surveillance, human-computer interfacing, networked camera conferencing, industrial monitoring or service and training applications. ISpace is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human following by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd. And the article presents the integration of color distributions into particle filtering. Particle filters provide a robust tracking framework under ambiguity conditions. We propose to track the moving objects by generating hypotheses not in the image plan but on the top-view reconstruction of the scene. Comparative results on real video sequences show the advantage of our method for multi-object tracking. Also, the method is applied to the intelligent environment and its performance is verified by the experiments.