Relevant bibliographies by topics / Particle filter

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Particle filter'

Author: Grafiati
Published: 4 June 2021
Last updated: 5 October 2024

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Journal articles on the topic "Particle filter"

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Liu, Jing Xian, De Qiang Chang, Yue Xie, Ning Mao, and Xi Sun. "Research on Fine Particles Capture of Baghouse Filter Media." Applied Mechanics and Materials 300-301 (February 2013): 1293–97. http://dx.doi.org/10.4028/www.scientific.net/amm.300-301.1293.

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Industrial dust emission is one of the main sources of fine particle especially for PM2.5 in atmosphere. Filter media is the key component for baghouse. In the paper, several normal needle felt filters and membrane filter are studied through experiments. The performances of filter such as resistance, capture efficiency for total particle and number counting efficiency for fine particle are tested.The experimental results show that the resistance of filter increase after aging, the resisitance increasing rate of membrane filter is the smallest; The efficiencies for total particles of normal filter are above 99.9% at clean state, and 99.99% at stable state after aging; Although the filters have high efficiency for total particle, but the number counting efficiency for 10μm particle is 94%-99%, and 52%-92% for 2μm particles. New filters for fine particles are needed.
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Kelly, Wayne, Donald Grant, and Joseph Zahka. "Optimization of Filter Properties for Recirculating Etch Baths." Journal of the IEST 43, no. 3 (June 14, 2000): 30–40. http://dx.doi.org/10.17764/jiet.43.3.72574h1883p177u4.

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Membrane filters are often used to remove small particles from liquids in recirculating etch baths (REBs). The ideal filter for this application would have both high particle capture efficiency and high flow permeability. Unfortunately, filters with high particle capture efficiency often have low permeability because the dominant particle capture mechanism is mechanical sieving. This paper describes more efficient capture mechanisms, interception and diffusion, and a filter with a surface modified to capture particles by these mechanisms. The filter has the same permeability as a conventional 0.45-μm filter and retains particles more efficiently than a conventional 0.05-μm filter. The filter is capable of removing multiple types of small (0.065-μm) particles (polystyrene latex, silicon nitride, alumina, etc.) with high efficiency (> 99.9 percent).
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Örenbaş, Halit, and Muharrem Mercimek. "Clustered Exact Daum-Huang Particle Flow Filter." Mathematical Problems in Engineering 2019 (May 13, 2019): 1–8. http://dx.doi.org/10.1155/2019/8369565.

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Unlike the conventional particle filters, particle flow filters do not rely on proposal density and importance sampling; they employ flow of the particles through a methodology derived from the log-homotopy scheme and ensure successful migration of the particles. Amongst the efficient implementations of particle filters, Exact Daum-Huang (EDH) filter pursues the calculation of migration parameters all together. An improved version of it, Localized Exact Daum-Huang (LEDH) filter, calculates the migration parameters separately. In this study, the main objective is to reduce the cost of calculation in LEDH filters which is due to exhaustive calculation of each migration parameter. We proposed the Clustered Exact Daum-Huang (CEDH) filter. The main impact of CEDH is the clustering of the particles considering the ones producing similar errors and then calculating the same migration parameters for the particles within each cluster. Through clustering and handling the particles with high errors, their engagement and influence can be balanced, and the system can greatly reduce the negative effects of such particles on the overall system. We implement the filter successfully for the scenario of high dimensional target tracking. The results are compared to those obtained with EDH and LEDH filters to validate its efficiency.
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Pei, Fujun, Mei Wu, and Simin Zhang. "Distributed SLAM Using Improved Particle Filter for Mobile Robot Localization." Scientific World Journal 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/239531.

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The distributed SLAM system has a similar estimation performance and requires only one-fifth of the computation time compared with centralized particle filter. However, particle impoverishment is inevitably because of the random particles prediction and resampling applied in generic particle filter, especially in SLAM problem that involves a large number of dimensions. In this paper, particle filter use in distributed SLAM was improved in two aspects. First, we improved the important function of the local filters in particle filter. The adaptive values were used to replace a set of constants in the computational process of importance function, which improved the robustness of the particle filter. Second, an information fusion method was proposed by mixing the innovation method and the number of effective particles method, which combined the advantages of these two methods. And this paper extends the previously known convergence results for particle filter to prove that improved particle filter converges to the optimal filter in mean square as the number of particles goes to infinity. The experiment results show that the proposed algorithm improved the virtue of the DPF-SLAM system in isolate faults and enabled the system to have a better tolerance and robustness.
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Papavasiliou, Anastasia. "A uniformly convergent adaptive particle filter." Journal of Applied Probability 42, no. 4 (December 2005): 1053–68. http://dx.doi.org/10.1239/jap/1134587816.

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Particle filters are Monte Carlo methods that aim to approximate the optimal filter of a partially observed Markov chain. In this paper, we study the case in which the transition kernel of the Markov chain depends on unknown parameters: we construct a particle filter for the simultaneous estimation of the parameter and the partially observed Markov chain (adaptive estimation) and we prove the convergence of this filter to the correct optimal filter, as time and the number of particles go to infinity. The filter presented here generalizes Del Moral's Monte Carlo particle filter.
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Papavasiliou, Anastasia. "A uniformly convergent adaptive particle filter." Journal of Applied Probability 42, no. 04 (December 2005): 1053–68. http://dx.doi.org/10.1017/s0021900200001108.

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Particle filters are Monte Carlo methods that aim to approximate the optimal filter of a partially observed Markov chain. In this paper, we study the case in which the transition kernel of the Markov chain depends on unknown parameters: we construct a particle filter for the simultaneous estimation of the parameter and the partially observed Markov chain (adaptive estimation) and we prove the convergence of this filter to the correct optimal filter, as time and the number of particles go to infinity. The filter presented here generalizes Del Moral's Monte Carlo particle filter.
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Zhang, Yinhang, Xiuhua Men, Shuai Wang, Xiuli Fu, and Liwen Chen. "CFD-DEM Study of Pleated Filter Plugging Process Based on Porous Media Model." Machines 10, no. 10 (September 26, 2022): 862. http://dx.doi.org/10.3390/machines10100862.

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The pneumatic conveying process of fine particles through filters was studied by CFD-DEM simulation method. The porous media model and porous structure were used to simulate the airflow state and the blocking effect of fine particles when they flowed through the filter. Under different particle feed rates and initial particle velocities, the effects of the plugging rate and settling velocity in pleated filters were analyzed, and the effect of particle deposition height on fluid zone was studied. The results showed that particles should avoid the feed rate of 250–750 g/s and choose the initial particle velocity of 3–6 m/s to achieve lower plugging rate and faster settling velocity. The position of the filter should avoid the particle inlet to avoid the increase of non-uniformity. Timely cleaning of particles in the filter box can improve the filtering performance.
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Kim, Inkyu, Nosan Kwak, Heoncheol Lee, and Beomhee Lee. "Improved particle fusing geometric relation between particles in FastSLAM." Robotica 27, no. 6 (January 6, 2009): 853–59. http://dx.doi.org/10.1017/s0263574708005250.

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SUMMARYFastSLAM is a framework for simultaneous localization and mapping using a Rao-Blackwellized particle filter (RBPF). But, FastSLAM is known to degenerate over time due to the loss of particle diversity, mainly caused by the particle depletion problem in resampling phase. In this work, improved particle filter using geometric relation between particles is proposed to restrain particle depletion and to reduce estimation errors and error variances. It uses a KD tree (k-dimensional tree) to derive geometric relation among particles and filters particles with importance weight conditions for resampling. Compared to the original particle filter used in FastSLAM, this technique showed less estimation error with lower error standard deviation in computer simulations.
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Lee, Yoonsang, and Andrew J. Majda. "State estimation and prediction using clustered particle filters." Proceedings of the National Academy of Sciences 113, no. 51 (December 5, 2016): 14609–14. http://dx.doi.org/10.1073/pnas.1617398113.

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Particle filtering is an essential tool to improve uncertain model predictions by incorporating noisy observational data from complex systems including non-Gaussian features. A class of particle filters, clustered particle filters, is introduced for high-dimensional nonlinear systems, which uses relatively few particles compared with the standard particle filter. The clustered particle filter captures non-Gaussian features of the true signal, which are typical in complex nonlinear dynamical systems such as geophysical systems. The method is also robust in the difficult regime of high-quality sparse and infrequent observations. The key features of the clustered particle filtering are coarse-grained localization through the clustering of the state variables and particle adjustment to stabilize the method; each observation affects only neighbor state variables through clustering and particles are adjusted to prevent particle collapse due to high-quality observations. The clustered particle filter is tested for the 40-dimensional Lorenz 96 model with several dynamical regimes including strongly non-Gaussian statistics. The clustered particle filter shows robust skill in both achieving accurate filter results and capturing non-Gaussian statistics of the true signal. It is further extended to multiscale data assimilation, which provides the large-scale estimation by combining a cheap reduced-order forecast model and mixed observations of the large- and small-scale variables. This approach enables the use of a larger number of particles due to the computational savings in the forecast model. The multiscale clustered particle filter is tested for one-dimensional dispersive wave turbulence using a forecast model with model errors.
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Michalski, Jacek, Piotr Kozierski, Wojciech Giernacki, Joanna Zietkiewicz, and Marek Retinger. "MultiPDF particle filtering in state estimation of nonlinear objects." Nonlinear Dynamics 106, no. 3 (October 25, 2021): 2165–82. http://dx.doi.org/10.1007/s11071-021-06913-2.

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AbstractThis paper presents a new particle filter algorithm (MultiPDF) for state estimation of nonlinear systems. The proposed method is a modification of the standard particle filter approach. Due to the strong need for the acceleration of calculations and an improvement in the estimation quality of state estimation, the authors propose a method which enables one to divide the main particle filter into smaller sub-filters with an accordingly smaller number of particles for each one of them. The algorithm has been implemented for various numbers of particles and subordinate parallel filters. Estimation quality has been checked for nine nonlinear objects (both one- and multidimensional) and evaluated through the quality index, average root-mean-squared error. The computation time of the particle filter algorithm for several hardware configurations has been compared. Based on the obtained results, it can be concluded that, besides the computation acceleration, the parallelization of the particle filter’s operation also improves the estimation quality.
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Dissertations / Theses on the topic "Particle filter"

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Cao, Hui. "Smoothed Particle Filter." INTELLIGENT MEDIA INTEGRATION NAGOYA UNIVERSITY / COE, 2005. http://hdl.handle.net/2237/10425.

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Morzfeld, Matthias, Daniel Hodyss, and Chris Snyder. "What the collapse of the ensemble Kalman filter tells us about particle filters." TAYLOR & FRANCIS LTD, 2017. http://hdl.handle.net/10150/623125.

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The ensemble Kalman filter (EnKF) is a reliable data assimilation tool for high-dimensional meteorological problems. On the other hand, the EnKF can be interpreted as a particle filter, and particle filters (PF) collapse in high-dimensional problems. We explain that these seemingly contradictory statements offer insights about how PF function in certain high-dimensional problems, and in particular support recent efforts in meteorology to 'localize' particle filters, i.e. to restrict the influence of an observation to its neighbourhood.
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Rane, Nikhil. "Isomap tracking with particle filter." Connect to this title online, 2007. http://etd.lib.clemson.edu/documents/1181252052/.

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Xia, Gongyi. "Particle Swarm Optimization and Particle Filter Applied to Object Tracking." Thesis, North Dakota State University, 2016. https://hdl.handle.net/10365/27610.

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The particle filter is usually used as a tracking algorithm in non-linear under the Bayesian tracking framework. However, the problems of degeneracy and impoverishment degrade its performance. The particle filter is thereafter enhanced by evolutionary optimization, in particular, Particle Swarm Optimization (PSO) is used in this thesis due to its capability of optimizing non-linear problems. In this thesis, the PSO enhanced particle filter is reviewed followed by an analysis of its drawbacks. Then, a novel sampling mechanism for the particle filter is proposed. This method generates particles via the PSO process and estimates the importance distribution from all the particles generated. This ensures that particles are located in high likelihood regions while still maintaining a certain level of diversity. This sampling mechanism is then used together with the marginal particle filter. The proposed method?s superiority in performance over the conventional particle filter is then demonstrated by simulations.
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Gebart, Joakim. "GPU Implementation of the Particle Filter." Thesis, Linköpings universitet, Reglerteknik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-94190.

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This thesis work analyses the obstacles faced when adapting the particle filtering algorithm to run on massively parallel compute architectures. Graphics processing units are one example of massively parallel compute architectures which allow for the developer to distribute computational load over hundreds or thousands of processor cores. This thesis studies an implementation written for NVIDIA GeForce GPUs, yielding varying speed ups, up to 3000% in some cases, when compared to the equivalent algorithm performed on CPU. The particle filter, also known in the literature as sequential Monte-Carlo methods, is an algorithm used for signal processing when the system generating the signals has a highly nonlinear behaviour or non-Gaussian noise distributions where a Kalman filter and its extended variants are not effective. The particle filter was chosen as a good candidate for parallelisation because of its inherently parallel nature. There are, however, several steps of the classic formulation where computations are dependent on other computations in the same step which requires them to be run in sequence instead of in parallel. To avoid these difficulties alternative ways of computing the results must be used, such as parallel scan operations and scatter/gather methods. Another area where parallel programming still is not widespread is the area of pseudo-random number generation. Pseudo-random numbers are required by the algorithm to simulate the process noise as well as for avoiding the particle depletion problem using a resampling step. In this thesis a recently published counter-based pseudo-random number generator is used.
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Käll, Viktor, and Erik Piscator. "Particle Filter Bridge Interpolation in GANs." Thesis, KTH, Matematisk statistik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-301733.

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Generative adversarial networks (GANs), a type of generative modeling framework, has received much attention in the past few years since they were discovered for their capacity to recover complex high-dimensional data distributions. These provide a compressed representation of the data where all but the essential features of a sample is extracted, subsequently inducing a similarity measure on the space of data. This similarity measure gives rise to the possibility of interpolating in the data which has been done successfully in the past. Herein we propose a new stochastic interpolation method for GANs where the interpolation is forced to adhere to the data distribution by implementing a sequential Monte Carlo algorithm for data sampling. The results show that the new method outperforms previously known interpolation methods for the data set LINES; compared to the results of other interpolation methods there was a significant improvement measured through quantitative and qualitative evaluations. The developed interpolation method has met its expectations and shown promise, however it needs to be tested on a more complex data set in order to verify that it also scales well.
Generative adversarial networks (GANs) är ett slags generativ modell som har fått mycket uppmärksamhet de senaste åren sedan de upptäcktes för sin potential att återskapa komplexa högdimensionella datafördelningar. Dessa förser en komprimerad representation av datan där enbart de karaktäriserande egenskaperna är bevarade, vilket följdaktligen inducerar ett avståndsmått på datarummet. Detta avståndsmått möjliggör interpolering inom datan vilket har åstadkommits med framgång tidigare. Häri föreslår vi en ny stokastisk interpoleringsmetod för GANs där interpolationen tvingas följa datafördelningen genom att implementera en sekventiell Monte Carlo algoritm för dragning av datapunkter. Resultaten för studien visar att metoden ger bättre interpolationer för datamängden LINES som användes; jämfört med resultaten av tidigare kända interpolationsmetoder syntes en märkbar förbättring genom kvalitativa och kvantitativa utvärderingar. Den framtagna interpolationsmetoden har alltså mött förväntningarna och är lovande, emellertid fordras att den testas på en mer komplex datamängd för att bekräfta att den fungerar väl även under mer generella förhållanden.
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Johansson, Henrik. "Road-constrained target tracking using particle filter." Thesis, Linköping University, Department of Electrical Engineering, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-11562.

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In this work a particle filter (PF) that uses a one-dimensional dynamic model to estimate the position of vehicles traveling on a road is derived. The dynamic model used in the PF is a second order linear-Gaussian model. To be able to track targets traveling both on and off road two different multiple model filters are proposed. One of the filters is a modified version of the Efficient Interacting Multiple Model (E-IMM) and the other is a version of the Multiple Likelihood Models (MLM). Both of the filters uses two modes, one for the on road motion and one for the off road motion. The E-IMM filter and the MLM filter are compared to the standard PF to be able to see the performance gain in using multiple models. This result indicates that the multiple model filters have better performance, at least when the true mode switching probabilities are used.


Den här arbetet presenterar ett partikelfilter som använder sig av en endimensionell dynamisk modell för att skatta positionen på fordon som befinner sig på någon väg. Den dynamiska modellen som används i partikelfiltret är en andra ordningens linjär-gaussisk modell. För att kunna spåra fordon som befinner sig både på och utanför vägen så föreslås två olika multipla filter. Ena filtret är en modifierad

variant av Efficient Interacting Multiple Model (E-IMM) och den andra är en version a Multiple Likelihood Models (MLM). Båda filtren använder sig av två moder, en för rörelse på vägen och en för rörelse utanför vägen. E-IMM filtret och MLM filtret jämförs med ett standard partikelfilter för att kunna se förbättringen vid använding av multipla modeller. Resultatet visar att båda multipla modell filtren ger bättre resultat, i varje fall då rätt sannolikheter för modbyte används.

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Tonetto, Leonardo. "A Particle Filter approach to GPS signals." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-177320.

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Localization systems nowadays are extensively used by a growing number of mobile devices, such as smartphones and tablets integrated with various applications, and their use for traditional purposes such as navigation and geodesy have pushed the development of new techniques and improved algorithms. The combination of multiple techniques is the most common approach. Global Navigation Satellite Systems, such as GPS are well known and established localization systems that have great accuracy but are limited to locations where the strength of the signal is good. Therefore a new approach that could increase the sensitivity and even the accuracy by using GPS could benet a large group of users. This thesis originally proposes a new approach for these signals, based on Particle Filters that proved to work well in mitigating problems in an audio-based localization system. The results obtained show that this approach can increase the sensitivity of the system as a whole and positions estimations can be achieved under conditions that previous systems were not able to.
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Raveendran, Palanivel. "Mechanisms of particle detachment during filter backwashing." Diss., Georgia Institute of Technology, 1993. http://hdl.handle.net/1853/18989.

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Watson, Paul David Julian. "Geotextile filter design and particle bridge formation." Thesis, Queen Mary, University of London, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.307520.

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Books on the topic "Particle filter"

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Dubuisson, Séverine. Tracking with Particle Filter for High-Dimensional Observation and State Spaces. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781119004868.

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Jonathan, Brandt, AWWA Research Foundation, and United States. Environmental Protection Agency., eds. Characterization of particles in filter effluents. Denver, CO: Awwa Research Foundation, 2007.

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Jonathan, Brandt, AWWA Research Foundation, and United States. Environmental Protection Agency., eds. Characterization of particles in filter effluents. Denver, CO: Awwa Research Foundation, 2007.

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Jonathan, Brandt, AWWA Research Foundation, and United States. Environmental Protection Agency., eds. Characterization of particles in filter effluents. Denver, CO: Awwa Research Foundation, 2007.

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Jonathan, Brandt, AWWA Research Foundation, and United States. Environmental Protection Agency., eds. Characterization of particles in filter effluents. Denver, CO: Awwa Research Foundation, 2007.

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Ristic, Branko. Particle Filters for Random Set Models. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-6316-0.

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Ristic, Branko. Particle Filters for Random Set Models. New York, NY: Springer New York, 2013.

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Stone, Lawrence D., Roy L. Streit, and Stephen L. Anderson. Introduction to Bayesian Tracking and Particle Filters. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-32242-6.

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Kolaru, Olukunle. An investigation into soil particle bridging in geotextile filters. [London]: Queen Mary and Westfield College, 1994.

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Lee, Rubow Kenneth, American Filtration Society, and American Filtration Society. Regional Meeting, eds. Fine particle filtration and separation. Houston: Gulf Pub. Co., 1991.

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Book chapters on the topic "Particle filter"

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Giron-Sierra, Jose Maria. "Kalman Filter, Particle Filter and Other Bayesian Filters." In Signals and Communication Technology, 3–148. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-2540-2_1.

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Davey, Samuel, Neil Gordon, Ian Holland, Mark Rutten, and Jason Williams. "Particle Filter Implementation." In SpringerBriefs in Electrical and Computer Engineering, 55–61. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0379-0_8.

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Bruno, Marcelo G. S. "Auxiliary Particle Filter." In Sequential Monte Carlo Methods for Nonlinear Discrete-Time Filtering, 47–48. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-031-02535-8_9.

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Nitti, Davide, Tinne De Laet, and Luc De Raedt. "Distributional Clauses Particle Filter." In Machine Learning and Knowledge Discovery in Databases, 504–7. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-44845-8_45.

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Zhang, Xiaoqin, Weiming Hu, and Steve Maybank. "A Smarter Particle Filter." In Computer Vision – ACCV 2009, 236–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12304-7_23.

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Schröder, Christina, Xingwen Wei, Undine Fischer, Gert Schmidt, Olena Volkova, and Christos G. Aneziris. "In Situ Observation of Collision Between Exogenous and Endogenous Inclusions on Steel Melts for Active Steel Filtration." In Multifunctional Ceramic Filter Systems for Metal Melt Filtration, 27–55. Cham: Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-40930-1_2.

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AbstractInvestigations at the high-temperature confocal laser scanning microscope (HT-CLSM) allow observing the interaction of non-metallic particles in terms of potential filter material with endogenous particles of molten steel in the high-temperature range. The respective particle velocities are determined from the particle movements and conclusions are drawn about the attractive forces of the particles. The interactions of exogenous Al2O3 particles, MgO and MgAl2O4 spinel particles, and CA6 calcium aluminate particles with endogenous constituents of molten steel X15CrNiSi25-20 are analyzed in the present work. Accompanying experiments were performed in a heating microscope on the interaction between steel and MgO and steel and CA6. Scanning electron microscopy SEM/EDX/EBSD studies reveal not only the interactions of the non-metallic inclusions with each other, but also reactions of the molten steel with the exogenous particles that affect the agglomeration behavior. While exogenous and endogenous Al2O3 particles exhibit high attractive forces and almost no react with the molten steel, a liquid reaction layer forms around the magnesia particles, which leads to a reduction of the attractive forces. After dissolution of the reaction layer, the attractive forces increase. Spinel particles are surrounded by a strong meniscus in the observed steel melt. Endogenous particles moving toward the spinel do not adhere to the particle. Reactions were also observed when CA6 particles came into contact with molten steel. In this process, the calcium aluminate is depleted of calcium. Only loose connections of the exogenous Ca-depleted CA6 with endogenous Al2O3 particles have been detected.
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Bain, Alan, and Dan Crisan. "A Continuous Time Particle Filter." In Stochastic Modelling and Applied Probability, 221–56. New York, NY: Springer New York, 2009. http://dx.doi.org/10.1007/978-0-387-76896-0_9.

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Goodrum, Matthew A., Michael J. Trotter, Alla Aksel, Scott T. Acton, and Kevin Skadron. "Parallelization of Particle Filter Algorithms." In Computer Architecture, 139–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24322-6_12.

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Wang, Qicong, Li Xie, Jilin Liu, and Zhiyu Xiang. "Enhancing Particle Swarm Optimization Based Particle Filter Tracker." In Lecture Notes in Computer Science, 1216–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/978-3-540-37275-2_151.

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Evensen, Geir, Femke C. Vossepoel, and Peter Jan van Leeuwen. "Particle Filter for Seismic-Cycle Estimation." In Springer Textbooks in Earth Sciences, Geography and Environment, 187–98. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-96709-3_19.

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AbstractThe particle filter is an effective data-assimilation method for low-dimensional, nonlinear systems. It is easy to implement, and it is straightforward to include model error, parameters, and controls in the state vector. This chapter demonstrates the use of a particle filter in the case of a parameter bias.
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Conference papers on the topic "Particle filter"

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Fan, Pengpai, Li-Fen Sui, Bing Wang, and Wei Wang. "Particle Filter-Weight Estimation and Dual Particle Filter." In 2009 International Workshop on Intelligent Systems and Applications. IEEE, 2009. http://dx.doi.org/10.1109/iwisa.2009.5073000.

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Wu, M., A. V. Kuznetsov, and W. Jasper. "Modeling Mass Transfer and Nanoparticle Capture in Electrostatically Charged Monolith Filters." In 2010 14th International Heat Transfer Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/ihtc14-22205.

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Analyzing trajectories of particles in monolith filters is important for predicting the capture efficiency and improving the design of this class of filters. Modeling and simulations of the particle trajectories are carried out to evaluate the probability of capture by the filter’s front surface and filter channel’s inner wall. Due to Brownian motion and electrostatic attraction, the particles exhibit a random walk and their trajectories deviate from the streamlines of the fluid flow. Particle trajectories are computed by the integration of Newton’s second law, where the electrostatic force, the Brownian motion force resulting from random collisions of the particle with air molecules, and the drag force from the surrounding fluid are all taken into account. A computer simulation for computing the particle trajectories and evaluating the probability of particle capture by the filter was developed. For this model, both flow field and electric field must be provided. The electric charge was assumed to be uniformly distributed along the edge of the channels of the filter and calculated numerically. The flow field is difficult to obtain due to the complex geometry of the model. The commercial CFD package ANSYS CFX [1] is used to compute the flow field. The resulting velocity flow field is then used to evaluate the drag force on the particles. We assume a one-way coupling between the fluid flow and the particle motion. Although there can be over one million uniformly distributed channels per square centimeter in the monolith filter, for simulation purposes, a single unit cell which models only one channel is used. The single unit model effectively describes the behavior of particles outside and inside the channels of monolith filter. The effects of different forces and different particle sizes were analyzed to investigate which factors affect the capture efficiency.
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Yunpeng Li, Lingling Zhao, and Mark Coates. "Particle flow auxiliary particle filter." In 2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP). IEEE, 2015. http://dx.doi.org/10.1109/camsap.2015.7383760.

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Comandur, Karthik, Yunpeng Li, and Santosh Nannuru. "Particle Flow Gaussian Particle Filter." In 2022 25th International Conference on Information Fusion (FUSION). IEEE, 2022. http://dx.doi.org/10.23919/fusion49751.2022.9841354.

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Murata, Masaya, Hidehisa Nagano, and Kunio Kashino. "Monte Carlo filter particle filter." In 2015 European Control Conference (ECC). IEEE, 2015. http://dx.doi.org/10.1109/ecc.2015.7330967.

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Viswanathan, Sandeep, Stephen S. Sakai, Mitchell Hageman, David E. Foster, Todd Fansler, Michael Andrie, and David A. Rothamer. "Effect of Particle Size Distribution on the Deep-Bed Capture Efficiency of an Exhaust Particulate Filter." In ASME 2014 Internal Combustion Engine Division Fall Technical Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/icef2014-5464.

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The exhaust filtration analysis system (EFA) developed at the University of Wisconsin – Madison was used to perform micro-scale filtration experiments on cordierite filter samples using particulate matter (PM) generated by a spark-ignition direct injection (SIDI) engine fueled with gasoline. A scanning mobility particle sizer (SMPS) was used to characterize running conditions with four distinct particle size distributions (PSDs). The distributions selected differed in the relative number of accumulation versus nucleation mode particles. The SMPS and an engine exhaust particle sizer (EEPS) were used to simultaneously measure the PSD downstream of the EFA and the real-time particulate emissions from the SIDI engine to determine the evolution of filtration efficiency during filter loading. Cordierite filter samples with properties representative of diesel particulate filters (DPFs) were loaded with PM from the different engine operating conditions. The results were compared to understand the impact of particle size distribution on filtration performance as well as the role of accumulation mode particles on the diffusion capture of PM. The most penetrating particle size (MPPS) was observed to decrease as a result of particle deposition within the filter substrate. In the absence of a soot cake, the penetration of particles smaller than 70 nm was seen to gradually increase with time, potentially due to increased velocities in the filter as flow area reduces during filter loading, or due to decreasing wall area for capture of particles by diffusion. Particle re-entrainment was not observed for any of the operating conditions.
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Jun, Liang, and Wu Yan. "Correlation particle filter." In 2017 13th IEEE International Conference on Electronic Measurement & Instruments (ICEMI). IEEE, 2017. http://dx.doi.org/10.1109/icemi.2017.8265904.

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Stano, Pawel, Zsofia Lendek, and Robert Babuska. "Saturated particle filter." In 2011 American Control Conference. IEEE, 2011. http://dx.doi.org/10.1109/acc.2011.5990757.

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Al-Hajeri, M. H., and A. Witry. "Computational Fluid Dynamics Investigation of Cylindrical Filter Element." In ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-85664.

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Cylindrical or candle filters have been developed for cleaning the hot combustion gas streams upstream of the turbine in a combined cycle power plant. To obtain continues operation a periodic cleaning is necessary and the cleaning efficiency depends on the distribution of the filtration cake. Consequently uniform particle deposition on the filter element surface is desired. The flow around three filter elements in cross flow is investigated computationally using the commercial code FLUENT. Three filter elements are placed in a two-dimensional rectangle duct with fixed face velocity and varying the velocity ratio between the approach and face velocity. Particle trajectories are obtained for a number of particle diameters and different inlet (approach) velocity to face filtration velocity ratios to investigate the behavior of particles around the filter element.
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Alderman, Steven, Michael Parsons, Kristina Hogancamp, O. Perry Norton, and Charles Waggoner. "Evaluation of the Effects of Media Velocity on HEPA Filter Performance." In The 11th International Conference on Environmental Remediation and Radioactive Waste Management. ASMEDC, 2007. http://dx.doi.org/10.1115/icem2007-7075.

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Section FC of the ASME AG-1 Code addresses glass fiber HEPA filters and restricts the media velocity to a maximum of 2.54 cm/s (5 ft/min). Advances in filter media technology allow glass fiber HEPA filters to function at significantly higher velocities and still achieve HEPA performance. However, diffusional capture of particles < 100 nm is reduced at higher media velocities due to shorter residence times within the media matrix. Therefore, it is unlikely that higher media velocities for HEPA filters will be allowed without data to demonstrate the effect of media velocity on removal of particles in the smaller size classes. In order to address this issue, static testing has been conducted to generate performance related data and a range of dynamic testing has provided data regarding filter lifetimes, loading characteristics, changes in filter efficiency and the most penetrating particle size over time. Testing was conducted using 31 cm × 31 cm × 29 cm deep pleat HEPA filters supplied from two manufacturers. Testing was conducted at media velocities ranging from 2.0–4.5 cm/s with a solid aerosol challenge composed of potassium chloride. Two set of media velocity data were obtained for each filter type. In one set of evaluations, the maximum aerosol challenge particle size was limited to 3 μm, while particles above 3 μm were not constrained in the second set. This provided for considerable variability in the challenge mass mean diameter and overall mass loading rate. Results of this testing will be provided to the ASME AG-1 FC Committee for consideration in future versions of the HEPA standard. In general, the initial filter efficiency decreased with increasing media velocity. However, initial filter efficiencies were generally good in all cases. Filter efficiency values averaged over the first ten minute of the loading cycle ranged from 99.970 to 99.996%. Additionally, the most penetrating particle size was observed to decrease with increasing media velocity, with initial values ranging from 194 to 134 nm.
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Reports on the topic "Particle filter"

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Taylor, S., J. Lever, K. Burgess, R. Stroud, D. Brownlee, L. Nittler, A. Bardyn, et al. Sampling interplanetary dust from Antarctic air. Engineer Research and Development Center (U.S.), February 2022. http://dx.doi.org/10.21079/11681/43345.

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We built a collector to filter interplanetary dust particles (IDPs) larger than 5 µm from the clean air at the Amundsen Scott South Pole station. Our sampling strategy used long duration, continuous dry filtering of near-surface air in place of short duration, high-speed impact collection on flags flown in the stratosphere. We filtered ~107 m³ of clean Antarctic air through 20 cm diameter, 3 µm filters coupled to a suction blower of modest power consumption (5–6 kW). Our collector ran continuously for 2 years and yielded 41 filters for analyses. Based on stratospheric concentrations, we predicted that each month’s collection would provide 300–900 IDPs for analysis. We identified 19 extraterrestrial (ET) particles on the 66 cm² of filter examined, which represented ~0.5% of the exposed filter surfaces. The 11 ET particles larger than 5 µm yield about a fifth of the expected flux based on >5 µm stratospheric ET particle flux. Of the 19 ET particles identified, four were chondritic porous IDPs, seven were FeNiS beads, two were FeNi grains, and six were chondritic material with FeNiS components. Most were <10 µm in diameter and none were cluster particles. Additionally, a carbon-rich candidate particle was found to have a small ¹⁵N isotopic enrichment, supporting an ET origin. Many other candidate grains, including chondritic glasses and C-rich particles with Mg and Si and FeS grains, require further analysis to determine if they are ET. The vast majority of exposed filter surfaces remain to be examined.
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Kerlin, M., E. Balboni, and K. Knight. Characterization, Chemistry, and Particle Size Distribution of Fallout Particles Isolated from Filter Samples. Office of Scientific and Technical Information (OSTI), March 2022. http://dx.doi.org/10.2172/1864128.

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Liu, Xinmin, Zongli Lin, and Scott Acton. A New Particle Filter Based Algorithm for Image Tracking. Fort Belvoir, VA: Defense Technical Information Center, July 2008. http://dx.doi.org/10.21236/ada501159.

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Williams, A., R. L. McCormick, R. Hayes, and J. Ireland. Biodiesel Effects on Diesel Particle Filter Performance: Milestone Report. Office of Scientific and Technical Information (OSTI), March 2006. http://dx.doi.org/10.2172/878457.

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Posselt, Derek J. Toward an Operational Particle Filter-Based Ensemble Data Assimilation System. Fort Belvoir, VA: Defense Technical Information Center, September 2014. http://dx.doi.org/10.21236/ada614557.

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Ahmadi, Goodarz. PARTICLE TRANSPORT AND DEPOSITION IN THE HOT-GAS FILTER AT WILSONVILLE. Office of Scientific and Technical Information (OSTI), June 1999. http://dx.doi.org/10.2172/793319.

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Goodarz Ahmadi. PARTICLE TRANSPORTATION AND DEPOSITION IN HOT GAS FILTER VESSELS - A COMPUTATIONAL AND EXPERIMENTAL MODELING APPROACH. Office of Scientific and Technical Information (OSTI), July 2002. http://dx.doi.org/10.2172/823418.

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Kilpatrick, L. L. Particle size distribution of ground ITP washed precipitate for estimating filter box radioactive cesium release during transfer. Office of Scientific and Technical Information (OSTI), October 1993. http://dx.doi.org/10.2172/10107805.

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Beal, Samuel, and Matthew Bigl. Particle size characteristics of energetic materials distributed from low-order functioning mortar munitions. Engineer Research and Development Center (U.S.), August 2024. http://dx.doi.org/10.21079/11681/49189.

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Particles of explosive filler distributed from low-order (LO) munition functioning are susceptible to dissolution and potential mobilization into groundwater and surface water. We command-initiated three mortar munitions as LO in triplicate using a fuze simulator and recovered particles from an ice surface to constrain LO particle characteristics. Total explosive mass recovery (19–55%) and spatial distribution (0->20 m) varied significantly both between munitions and between replicate LOs of the same munition. The median particle size (0.27–3.99 mm) varied with total mass recovery. In general, LO particles coarsened, and total mass deposition rates decreased logarithmically, with increasing distance from the initiation point.
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Lawson. L51597 Feasibility Study of New Technology for Intake Air Filtration. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), June 1989. http://dx.doi.org/10.55274/r0010105.

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Inlet air filters are widely used to remove solids and liquid droplets from the ambient air before it enters the compressor of a gas turbine. Clean inlet air provides many advantages: Less corrosion of the compressor and of gas-path hot parts, such as the turbine, decreased compressor fouling, less erosion of the compressor bladeThese in turn prevent deterioration of output and heat rate, and reduce maintenance costs. Compressor fouling is caused by the ingestion of substances that deposit and adhere to blade surfaces, resulting in reduced aerodynamic efficiency and decreased available output. Air contamination could be significantly reduced by the use of more efficient air filtration systems, especially through the reduction of the quantity of smaller particles ingested. The consequent lower loss of output power and decreased cleaning efforts provide lower costs of operation and increased shaft power. This work was composed of three major efforts: 1) A literature search was performed to establish the state of the art for particle removal from gases, particularly by electrostatic precipitation, and to identify the leading vendors of the equipment-considering both experience and technical expertise. 2) Two chosen companies were visited to determine their technical capabilities as they apply to gas turbine inlet air filtration. 3) A representative gas turbine was specified by PRCI as being the equivalent of a GE Model 3002J turbine, with airflow of 91,200 acfm. A specification based upon that airflow was prepared and submitted to the two vendors. Each vendor prepared a proposal for a filter system compliant with the specification. The proposed air filtration equipment is sufficiently different from existing products that it was judged not beneficial to visit manufacturing facilities. Both vendors are reputable suppliers of air filtration equipment. This study is intended to provide definitive information relative to the use of new technology for air inlet filtration on gas turbines in gas pipeline pumping applications.
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