• Journal of Advanced Navigation Technology
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• v.15 no.4
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• pp.556-561
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• 2011

It is generally known that particle filters can produce consistent target tracking performance in comparison to the Kalman filter for non-linear and non-Gaussian systems. In this paper, I propose a Rao-Blackwellized multiple model particle filter(RBMMPF) to enhance computational efficiency of the particle filters as well as to reduce sensitivity of modeling. Despite that the Rao-Blackwellized particle filter needs less particles than general particle filter, it has a similar tracking performance with a less computational load. Comparison results for performance is listed for the using single sensor information RBMMPF and using multisensor data fusion RBMMPF.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.6
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• pp.644-655
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• 2012

As soon as a new air filter is applied to an air purification process, the filter gets loaded with dust particles. Thus, the study on the particle loading characteristics of air filter is very essential in order to understand the real filtration phenomena during filter use. In this study, we investigated the effect of particle and filter charge on the particle loading property of air filter. Charged filter and uncharged filter prepared by discharging the charged filter by isopropyl alcohol were used as test samples, and three types of particle having different charge states were supplied to filters tested. For neutralized particles there was a big difference in areal mass loading rates between charged and uncharged filters due to the very small amount of particle charge, on the other hand the difference was diminished for atomized particle and finally almost vanished for corona charged particles. The pressure drop of filter loaded with corona charged particles was only half of those for neutralized and atomized particles at the same areal mass loading because of the porous structure of particle deposit formed on filter fibers, caused by the space charge effect between particles.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.05a
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• pp.245-248
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• 2006

A particle filter is one of the most famous filters. The reason why the particle filter is widely used is that particle deals with the state estimation problem for not only linear models with Gaussian noise but also the non-linear models with non-Gaussian noise and it receives great attention from many engineering fields. In the point of view state estimator, particle filter is feedforward observer. According to the characteristic of dynamic system, the feedforward observer can estimate real state. However, the speed of convergence of feedforward observer between the actual state and the estimated state cannot be satisfied. Since the particle filter is a sort of feedforward observer, the convergence speed of particle filter is slow, and the particle filter cannot estimate actual state like particle collapse problem. In order to overcome the limitation of particle filter as a kind of feedfoward estimator, we propose a new particle filter which has feedback term, called particle filter with feedback. Our proposed method is analyzed theoretically and studied by computer simulation. Comparisons are made with other filtering mehod.

• ETRI Journal
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• v.45 no.3
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• pp.394-403
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• 2023

Direct tracking problem of moving noncircular sources for multiple arrays is investigated in this study. Here, we propose an improved unscented particle filter (I-UPF) direct tracking method, which combines system proportional symmetry unscented particle filter and Markov Chain Monte Carlo (MCMC) algorithm. Noncircular sources can extend the dimension of sources matrix, and the direct tracking accuracy is improved. This method uses multiple arrays to receive sources. Firstly, set up a direct tracking model through consecutive time and Doppler information. Subsequently, based on the improved unscented particle filter algorithm, the proposed tracking model is to improve the direct tracking accuracy and reduce computational complexity. Simulation results show that the proposed improved unscented particle filter algorithm for noncircular sources has enhanced tracking accuracy than Markov Chain Monte Carlo unscented particle filter algorithm, Markov Chain Monte Carlo extended Kalman particle filter, and two-step tracking method.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.6
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• pp.760-768
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• 2000

Filter efficiency of electrically charged particle in uncharged fibrous filter was measured. In previous studies, the effect of charged particle on filter efficiency was investigated but there was difficulty in measuring of image effect that is appeared at the charged small particle. We could easily measure the image effect with charging small particles by photoelectric charging. The spark discharge aerosol generator and a differential mobility analyzer (DMA) were used to generate sub-micron monodisperse particles (${\leq}200$ nm). The generated particles were charged in photoelectric charging process using ultraviolet lamp and electric field. The filter efficiency of the charged particles, classified by another DMA, was measured in filter tester using a condensation nucleus counter (CNC) as function of particle diameter, particle charge and airflow velocity. It is shown that the filter efficiency increases with increasing charge number of the particle and is affected by particle size and flow velocity. Single fiber filter efficiency mainly depends on image force parameter and peclet number. The peclet number was not considered at previous other papers. We propose a modi fied experimental correlation as function of image force parameter and peclet number.

• Particle and aerosol research
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• v.12 no.4
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• pp.151-159
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• 2016

Since airborne viruses have been known to aggravate indoor air quality, studies on development of anti-viral air filter increase recently. In this study, a mass aerosol particle generator for coating a commercial air filter (over $300{\times}300mm^2$) was built, and evaluated by comparing a commercial particle generator. Then, via this device, a commercial air filter was coated with anti-viral material ($SiO_2-Ag$ nanoparticles in this study), so fabrication of commercial anti-viral air filter was performed and the pressure drop, filtration efficiency, and anti-viral ability of the filter were evaluated against aerosolized bacteriophage MS2 in a continuous air flow condition. The result showed that the particle generation of the new generator was more than about 8.5 times over which of the commercial one. Consequently, $SiO_2-Ag$ particle coating on a filter does not have significant effects on the filtration efficiency and pressure drop with different areas, and the average anti-viral efficiency of the $SiO_2-Ag$ filter was about 92% when the coating areal density was $1.0{\times}10^{12}particles/m^2$.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.14 no.10
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• pp.792-800
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• 2002

A grease filter is used to remove grease generated from a cooking appliance in a kitchen. This numerical study has been conducted to investigate the particle collection characteristics of a grease filter having nominal flowrate of $100m^3$/h. The flow field and particle trajectories in the grease filter with a flow chamber were simulated by using the commercial code of STAR-CD. The air velocity and pressure distributions were discussed in detail. The pressure drop of a grease filter rapidly increases with increasing the air flowrate. The numerical values of the pressure drop are slightly lower than the experimental values when the air flowrates are 50, 75, and 100㎥/h. The particle collection efficiency of a grease filter increases with increasing the particle diameter, the particle density, and the air flowrate, which means that the inertial impaction is a dominant particle removal mechanism in a grease filter. The cut-off diameter of the tested grease filter representing 50-% collection efficiency is about 11.6$\mu$m for water droplets at $100m^3$/h.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.710-726
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• 2018

This paper presents an extended particle filter to increase the accuracy and decrease the computation load of vehicle tracking. Particle filter has been the subject of extensive interest in video-based tracking which is capable of solving nonlinear and non-Gaussian problems. However, there still exist problems such as preventing unnecessary particle consumption, reducing the computational burden, and increasing the accuracy. We aim to increase the accuracy without an increase in computation load. In proposed method, we calculate the direction angle of the target vehicle. The angular difference between the direction of the target vehicle and each particle of the particle filter is observed. Particles are filtered and weighted, based on their angular difference. Particles with angular difference greater than a threshold is eliminated and the remaining are stored with greater weights in order to increase their probability for state estimation. Threshold value is very critical for performance. Thus, instead of having a constant threshold value, proposed algorithm updates it online. The first advantage of our algorithm is that it prevents the system from failures caused by insufficient amount of particles. Second advantage is to reduce the risk of using unnecessary number of particles in tracking which causes computation load. Proposed algorithm is compared against camshift, direction-based particle filter and condensation algorithms. Results show that the proposed algorithm outperforms the other methods in terms of accuracy, tracking duration and particle consumption.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.6
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• pp.867-872
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• 2009

In centrifugal oil filters particles are forced to move toward the filter casing wall by centrifugal force in the rotating oil flow and the particles are trapped and removed on the filter paper installed at the wall. In the present study, flow field of oil and particle motion in a centrifugal oil filter has been numerically calculated in order to estimate the filtering efficiency for various operating conditions. Fluent code was used for the numerical calculations. Uncoupling the oil flow and the particle motion and the use of particle tracking trajectory enabled the estimation of filtering efficiency for various particle sizes, particle density and the filter rotational speed. Higher filtering efficiency was observed for heavier and larger particles as well as higher filter rotational speed. For the typical case of the particle density of $6000kg/m^3$ and the particle size of $10{\mu}m$ at 3500 RPM, the calculated filtering efficiency per passage was 0.31.

• Korean Chemical Engineering Research
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• v.44 no.3
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• pp.294-299
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• 2006

Computational simulation was performed to analyze flow velocities and particle trajectories onto the surface of bag-shaped filters with a different permeability. When the permeability of a filter is lower than that of a low-efficient fabric bag-filter widely used, the distributions of flow velocities and particle trajectories on the filter surface were not different with decreasing the filter permeability. The distributions of streamlines and radial directional gas velocities were uniform on the filter surface except for the neighbors of the bottom edge and outlet of the filter. The particle trajectories onto filter surface were more densely distributed around the bottom edge of the filter, so that the particle number on the filter surface was maximized near the bottom edge and decreased in the direction of the filter outlet.