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Articoli di riviste sul tema "Particle filter"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 25 luglio 2025

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1

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 fil

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2

Kelly, Wayne, Donald Grant, and Joseph Zahka. "Optimization of Filter Properties for Recirculating Etch Baths." Journal of the IEST 43, no. 3 (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

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3

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 i

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4

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 calculati

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5

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 (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

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6

Papavasiliou, Anastasia. "A uniformly convergent adaptive particle filter." Journal of Applied Probability 42, no. 4 (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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7

Papavasiliou, Anastasia. "A uniformly convergent adaptive particle filter." Journal of Applied Probability 42, no. 04 (2005): 1053–68. http://dx.doi.org/10.1017/s0021900200001108.

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Abstract (sommario):

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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8

Kim, Inkyu, Nosan Kwak, Heoncheol Lee, and Beomhee Lee. "Improved particle fusing geometric relation between particles in FastSLAM." Robotica 27, no. 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

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9

Lee, Yoonsang, and Andrew J. Majda. "State estimation and prediction using clustered particle filters." Proceedings of the National Academy of Sciences 113, no. 51 (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 s

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10

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 (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. E

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11

Fan, Ying, Yonggang Zhang, Guoqing Wang, Xiaoyu Wang, and Ning Li. "Maximum Correntropy Based Unscented Particle Filter for Cooperative Navigation with Heavy-Tailed Measurement Noises." Sensors 18, no. 10 (2018): 3183. http://dx.doi.org/10.3390/s18103183.

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In this paper, a novel robust particle filter is proposed to address the measurement outliers occurring in the multiple autonomous underwater vehicles (AUVs) based cooperative navigation (CN). As compared with the classic unscented particle filter (UPF) based on Gaussian assumption of measurement noise, the proposed robust particle filter based on the maximum correntropy criterion (MCC) exhibits better robustness against heavy-tailed measurement noises that are often induced by measurement outliers in CN systems. Furthermore, the proposed robust particle filter is computationally much more eff

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12

Kobler, Daniel, and Markus Boller. "Particle removal in different filtration systems for tertiary wastewater treatment - a comparison." Water Science and Technology 36, no. 4 (1997): 259–67. http://dx.doi.org/10.2166/wst.1997.0133.

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In seven wastewater installations in the area of Zürich, Switzerland, four different filtration systems for tertiary wastewater treatment (deep bed, cloth drum, continuous up-flow and cell filters) were investigated with special attention to particle size distributions in the in- and outflow of the flocculation and the filtration step. Flocculation and filter performance was characterised by the shift of particle number curves. For each filter, particle number, surface and volume removal as a function of particle size was determined and revealed to be an excellent tool to evaluate the filter p

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13

Chow, Judith C., John G. Watson, Xiaoliang Wang, Behrooz Abbasi, Wm Randolph Reed, and David Parks. "Review of Filters for Air Sampling and Chemical Analysis in Mining Workplaces." Minerals 12, no. 10 (2022): 1314. http://dx.doi.org/10.3390/min12101314.

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This review considers the use of filters to sample air in mining workplace environments for dust concentration measurement and subsequent analysis of hazardous contaminants, especially respirable crystalline silica (RCS) on filters compatible with wearable personal dust monitors (PDM). The review summarizes filter vendors, sizes, costs, chemical and physical properties, and information available on filter modeling, laboratory testing, and field performance. Filter media testing and selection should consider the characteristics required for mass by gravimetry in addition to RCS quantification b

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14

Lee, Jae-Keun, Benjamin Liu, Kenneth Rubow, and Seong-Ho Yoo. "Filtration of Real-World Particles in Liquids by Microporous Membrane Filters." Journal of the IEST 38, no. 3 (1995): 19–25. http://dx.doi.org/10.17764/jiet.2.38.3.3187876094028675.

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The filtration effect of irregular-shaped, real-world particles, such as silicon, alumina, and silicon nitride particles, has been experimentally investigated using 0.1, 0.22, and 0.45-μm-rated polyvinylidence difluoride (PVDF) and 0.2-μm polytetrafluoroethylene (PTFE) membrane filters. Particle retention tests were performed by measuring particle concentrations upstream and downstream of the test filter using an automatic liquid-borne laser particle counter (LPC). The test apparatus for the particle retention studies used a pump-driven water recirculating system. Zeta potential values play an

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15

Suoth, Verna Albert, and Maria D. Bobanto. "PENGUKURAN KONSENTRASI PARTIKEL ASAP ROKOK DENGAN MENGGUNAKAN P-TRAK." JURNAL ILMIAH SAINS 16, no. 2 (2016): 80. http://dx.doi.org/10.35799/jis.16.2.2016.14109.

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ABSTRAK Penelitian ini bertujuan untuk menentukan konsentrasi partikel pada asap rokok pada beberapa sampel rokok yang menggunakan filter dan sampel rokok tersebut merupakan rokok yang beredar di Indonesia. Ada 4 sampel rokok berfilter yang digunakan yakni filter x, filter B, filter DE, dan filter DF. Jumlah konsentrasi partikel asap rokok diukur dengan menggunakan P-Track. Hasil penelitian yang di dapat bervariasi bergantung dari karakteristik filter yang ada pada masing-masing rokok tersebut. Konsentrasi partikel asap rokok yang terukur dengan menggunakan beberapa filter didapatkan bahwa den

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16

Jiao, Ziquan, Zhiqiang Feng, Na Lv, Wenjing Liu, and Haijian Qin. "Improved Particle Filter Using Clustering Similarity of the State Trajectory with Application to Nonlinear Estimation: Theory, Modeling, and Applications." Journal of Sensors 2021 (May 26, 2021): 1–19. http://dx.doi.org/10.1155/2021/9916339.

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A clustering similarity particle filter based on state trajectory consistency is presented for the mathematical modeling, performance estimation, and smart sensing of nonlinear systems. Starting from an information fusion model based on the consistency principle of the spatial state trajectory, the predicted observation information of the current particle filter (original trajectory) and future multistage Gaussian particle filter (modified trajectory) are selected as the state trajectories of the sampling particles. Clustering similarity methods are used to measure the state trajectories of th

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17

Liu, Fanming, Fangming Li, and Xin Jing. "INS/gravity gradient aided navigation based on gravitation field particle filter." Open Physics 17, no. 1 (2019): 709–18. http://dx.doi.org/10.1515/phys-2019-0073.

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Abstract Swarm intelligence method is an effective way to improve the particle degradation and sample depletion of the traditional particle filter. This paper proposes a particle filer based on the gravitation field algorithm (GF-PF), and the gravitation field algorithm is introduced into the resampling process to improve particle degradation and sample depletion. The gravitation field algorithm simulates the solar nebular disk model, and introduces the virtual central attractive force and virtual rotation repulsion force between particles. The particles are moves rapidly to the high-likelihoo

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18

Sweeney, Daniel, Cigdem Keles, and Emily Sarver. "Exploring the Effect of Particle Loading Density on Respirable Dust Classification by SEM-EDX." Minerals 14, no. 7 (2024): 728. http://dx.doi.org/10.3390/min14070728.

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Exposure to respirable coal mine dust (RCMD) still poses health risks to miners. Scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX) is a powerful tool for RCMD characterization because it provides particle-level data, including elemental ratios (via the EDX signals) that can enable classification by inferred mineralogy. However, if the particle loading density (PLD) is high on the analyzed substrate (filter sample), interference between neighboring particles could cause misclassification. To investigate this possibility, a two-part study was conducted. First, the

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19

Abdullahi Daniyan. "Robust Multi-Target Tracking with a Kalman-Gain CPHD Filter: Simulation and Experimental Validation." World Journal of Advanced Engineering Technology and Sciences 15, no. 1 (2025): 1636–47. https://doi.org/10.30574/wjaets.2025.15.1.0369.

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We introduce a novel cardinalized implementation of the Kalman-gain-aided particle probability hypothesis density (KG-SMC-PHD) filter, extending it to form the Kalman-Gain Particle Cardinalized Probability Hypothesis Density (KG-SMC-CPHD) filter. This new approach significantly enhances multi-target tracking by combining the particle-based state correction mechanism with the propagation of both the PHD and target cardinality distribution. Unlike conventional particle filters that require a large number of particles for acceptable performance, our method intelligently corrects selected particle

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20

Hou, Yu Bao, and Shu Yan Tang. "Breeding Estimated Particle Filter." Advanced Materials Research 740 (August 2013): 332–37. http://dx.doi.org/10.4028/www.scientific.net/amr.740.332.

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As the normal particle filter has an expensive computation and degeneracy problem, a propagation-prediction particle filter is proposed. In this scheme, particles after transfer are propagated under the distribution of state noise, and then the produced filial particles are used to predict the corresponding parent particle referring to measurement, in which step the newest measure information is added into estimation. Therefore predicted particle would be closer to the true state, which improves the precision of particle filter. Experiment results have proved the efficiency of the algorithm an

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21

KIRSH, V. A., and A. A. KIRSH. "COLLECTION OF SUBMICRON AEROSOL PARTICLES BY FILTERS COMPOSED OF NANOFIBERS." Коллоидный журнал 85, no. 1 (2023): 38–46. http://dx.doi.org/10.31857/s0023291222600316.

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The deposition of aerosol particles from a Stokes flow in filters composed of nanofibers has been considered at Knudsen numbers Kn ∼ 1. The efficiency of particle collection by model filters with 2D and 3D structures has been determined by numerical simulation as depending on particle radius rp , filter parameters (nanofiber radius a, packing density α and filter thickness), and filtration conditions taking into account the gas slip at the fibers.It has been shown that the efficiencies of particle collection by nanofibers in model 2D and 3D filters are almost equal at the same low packing dens

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22

Lee, Jae-Keun, Benjamin Liu, and Kenneth Rubow. "Latex Sphere Retention by Microporous Membranes in Liquid Filtration." Journal of the IEST 36, no. 1 (1993): 26–36. http://dx.doi.org/10.17764/jiet.2.36.1.3013036291k8n475.

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An experimental study of particulate matter retention by microporous membranes during liquid filtration has been conducted using 0.1, 0.22, 0.45, and 0.65-μm-rated hydrophilic and hydrophobic membrane filters. Retention measurements have been made with polystyrene latex spheres using an automated filter test system and a laser particle counter to measure the upstream and downstream particle concentration. Particle filtration during loading tests was found to begin with a sieving dominant regime followed by a transition regime and a cake filtration regime as particles accumulate inside the filt

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23

Li, Xin, Yan Wang, and Dawei Liu. "Research on Extended Kalman Filter and Particle Filter Combinational Algorithm in UWB and Foot-Mounted IMU Fusion Positioning." Mobile Information Systems 2018 (July 3, 2018): 1–17. http://dx.doi.org/10.1155/2018/1587253.

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As UWB high-precision positioning in NLOS environment has become one of the hot topics in the research of indoor positioning, this paper firstly presents a method for the smoothing of original range data based on the Kalman filter by the analysis of the range error caused by UWB signals in LOS and NLOS environment. Then, it studies a UWB and foot-mounted IMU fusion positioning method with the integration of particle filter with extended Kalman filter. This method adopts EKF algorithm in the kinematic equation of particle filters algorithm to calculate the position of each particle, which is li

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24

Li, Hai Xia, Zhi Jun Sun, Li Jun Zhao, and Zhan Xu Tie. "Filtration and Pulse Cleaning System for Particle Removal from Gas." Applied Mechanics and Materials 42 (November 2010): 188–91. http://dx.doi.org/10.4028/www.scientific.net/amm.42.188.

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The application of rigid ceramic filter for gas filtration on an industrial scale has shown unstable operation over periods of days. The behavior of the ceramic filtration in further application can be predict by measuring properties of a variety of dust and filtration operation condition. The aim of the experimental investigation is to analysis the pressure distribution inside and outside the ceramic filter along the filter length, and to analyze the pressure drop across the filter along the filter length. Ceramic filter filtration system composes multi-pipe filters for gas clean up is introd

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25

Long, Yangjuan, Zhenji Liu, Quanli Zong, Heyi Jing, and Chen Lu. "Study on the Structural Characteristics of Mesh Filter Cake in Drip Irrigation: Based on the Growth Stage of Filter Cake." Agriculture 14, no. 8 (2024): 1296. http://dx.doi.org/10.3390/agriculture14081296.

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Mesh filters are frequently employed in water-saving irrigation fields. Studies addressing the method of cake formation and the characteristics of the cake during the mesh filter’s growing phase are still missing. One-way and orthogonal experiments were carried out using mesh filters with 220 μm and 320 μm aperture sizes as the research objects, taking particle concentrations, inlet flow, and growth phases as experimental factors. According to the variation rule of seed pressure drop in the formation process of filter cake, the growth process of filter cake is divided into four stages, which a

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26

Gorczyca, Beata, and David London. "Characterization of Particles in Slow Sand Filtration at North Caribou Water Treatment Plant." Water Quality Research Journal 38, no. 1 (2003): 153–68. http://dx.doi.org/10.2166/wqrj.2003.010.

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Abstract Microscopic analysis of particles in water can indicate the size of filter media required, and can be used to monitor filter performance. This study investigated a malfunctioning slow sand filter in a water treatment facility on a First Nations community in Northern Ontario. There has been a boil-water advisory in the community due to high turbidity in the drinking water since the plant was put into operation. Also, the slow sand filters in the plant clog frequently resulting in outflow volumes significantly below the plant design capacity. On-line particle counts and microscopic anal

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Wang, Er Shen, Tao Pang, and Zhi Xian Zhang. "Accuracy Improvement of GPS Positioning Based on GA-Aided Particle Filter." Applied Mechanics and Materials 719-720 (January 2015): 737–43. http://dx.doi.org/10.4028/www.scientific.net/amm.719-720.737.

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Aiming at the weight degeneracy phenomena in particle filter algorithm, a resampling method improving the diversity based on GA-aided particle filter was presented. Taking the advantage of genetic algorithm ( GA ) in selection ,crossover and inheritance to make up for the shortcoming of resampling. Genetic operation on particles in real number domain is adapted to reduce the complex of the genetic algorithm. And the evolutionary idea of genetic algorithm was combined with particle filter, by using selection, and mutation to improve the weight degeneracy and diversity of particle filter. This G

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Yao, Hai Tao, Hai Qiang Chen, and Tuan Fa Qin. "Niche PSO Particle Filter with Particles Fusion for Target Tracking." Applied Mechanics and Materials 239-240 (December 2012): 1368–72. http://dx.doi.org/10.4028/www.scientific.net/amm.239-240.1368.

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An improved particle filter algorithm is proposed to track a randomly moving target in video. In particle filter framework, a particle swarm optimization improved by niche technique which implemented by restricted competition selection is integrated. It can move particles into high likelihood area of target and form multi-population distribution, so that the searching capability of particles is enhanced and then the adaptation to the change of dynamic target state is improved. The particles of niching particle swarm optimization and the particles of particle filter are integrated for new parti

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Gui, Yi, and Nong Cheng. "An Improved Approach of Terrain-Aided Navigation Based on RBPF." Applied Mechanics and Materials 336-338 (July 2013): 336–42. http://dx.doi.org/10.4028/www.scientific.net/amm.336-338.336.

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Rao-Blackwellized Particle Filter (RBPF) is suitable for solving the linear/nonlinear mixed Terrain-Aided Navigation (TAN) problem. But the Particle Filter (PF) part of RBPF is Standard Particle Filter (SPF), causing particle diversity reduction and even filters divergence under extreme conditions. To get a better estimation of the errors of INS, this paper proposes an improved approach called Regularized Rao-Blackwellized Particle Filter (RRBPF). After updating the nonlinear state and corresponding importance weights, RRBPF resamples from the Epanechnikov kernel and then get the resampled par

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Xue, Changhu, Guigen Nie, Haiyang Li, and Jing Wang. "Data assimilation with an improved particle filter and its application in the TRIGRS landslide model." Natural Hazards and Earth System Sciences 18, no. 10 (2018): 2801–7. http://dx.doi.org/10.5194/nhess-18-2801-2018.

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Abstract. Particle filters have become a popular algorithm in data assimilation for their ability to handle nonlinear or non-Gaussian state-space models, but they have significant disadvantages. In this work, an improved particle filter algorithm is proposed. To overcome the particle degeneration and improve particles' efficiency, the processes of particle resampling and particle transfer are updated. In this improved algorithm, particle propagation and the resampling method are ameliorated. The new particle filter is applied to the Lorenz-63 model, and its feasibility and effectiveness are ve

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Hoteit, I., D.-T. Pham, G. Triantafyllou, and G. Korres. "A New Approximate Solution of the Optimal Nonlinear Filter for Data Assimilation in Meteorology and Oceanography." Monthly Weather Review 136, no. 1 (2008): 317–34. http://dx.doi.org/10.1175/2007mwr1927.1.

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Abstract This paper introduces a new approximate solution of the optimal nonlinear filter suitable for nonlinear oceanic and atmospheric data assimilation problems. The method is based on a local linearization in a low-rank kernel representation of the state’s probability density function. In the resulting low-rank kernel particle Kalman (LRKPK) filter, the standard (weight type) particle filter correction is complemented by a Kalman-type correction for each particle using the covariance matrix of the kernel mixture. The LRKPK filter’s solution is then obtained as the weighted average of sever

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Kim, J., and J. E. Tobiason. "Origins of filter effluent particles: experimental study of particle deposition and detachment." Water Science and Technology 50, no. 12 (2004): 215–22. http://dx.doi.org/10.2166/wst.2004.0716.

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This paper investigates the relative roles of particle deposition and detachment in controlling the origin of filter effluent particles. A conceptual mathematical model was developed and laboratory-scale experiments were conducted. Laboratory experiments were performed using three sizes of fluorescent microspheres (FMs), to determine the fraction of filter effluent particles that are filter influent particles that were never removed, as well as the fraction of filter effluent particles that were detached after deposition. Experimental results indicated that particle detachment is significant b

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Zhang, Wenzheng, Jiumao Cai, Guoliang Zhai, Lei Song, and Mouchao Lv. "Experimental Study on the Filtration Characteristics and Sediment Distribution Influencing Factors of Sand Media Filters." Water 15, no. 24 (2023): 4303. http://dx.doi.org/10.3390/w15244303.

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The sand media filter is a crucial component of micro-irrigation filtration systems. Investigating the effects of various factors on filtration performance and the migration patterns of sediment particles within the filter can enhance the healthy operation of sand media filters. This study, based on a sand media filter model, conducts indoor hydraulic experiments, selecting different experimental factors and observation indices for research under varying conditions. Results indicate that filter thickness and raw water concentration are positively correlated with the turbidity of filtered water

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Christensen, Morten Lykkegaard, Morten Møller Klausen, and Peter Vittrup Christensen. "Test of precoat filtration technology for treatment of swimming pool water." Water Science and Technology 77, no. 3 (2017): 748–58. http://dx.doi.org/10.2166/wst.2017.593.

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Abstract The technical performance of a precoat filter was compared with that of a traditional sand filter. Particle concentration and size distribution were measured before and after the filtration of swimming pool water. Both the sand and precoat filters could reduce the particle concentration in the effluent. However, higher particle removal efficiency was generally observed for the precoat filter, especially for particles smaller than 10 μm in diameter. Adding flocculant improved the removal efficiency of the sand filter, resulting in removal efficiencies comparable to those of the precoat

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Naddeo, V., and V. Belgiorno. "Tertiary filtration in small wastewater treatment plants." Water Science and Technology 55, no. 7 (2007): 219–25. http://dx.doi.org/10.2166/wst.2008.148.

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Tertiary filtration can be proposed in small wastewater treatment plants with impact on protected water bodies. Rotating disk filters may be adopted, in respect to conventional sand filters, when low availability of space and low investment costs are the prevailing conditions. The overall objective of this research was to evaluate the filtration efficiency of rotating disk filters; to compare effectiveness with traditional sand filters; to analyse thoroughly the importance of particle size distribution in wastewater tertiary filtration. In the experimental activity, conventional wastewater qua

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Feng, Jie, Xuguang Wang, and Jonathan Poterjoy. "A Comparison of Two Local Moment-Matching Nonlinear Filters: Local Particle Filter (LPF) and Local Nonlinear Ensemble Transform Filter (LNETF)." Monthly Weather Review 148, no. 11 (2020): 4377–95. http://dx.doi.org/10.1175/mwr-d-19-0368.1.

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AbstractThe local particle filter (LPF) and the local nonlinear ensemble transform filter (LNETF) are two moment-matching nonlinear filters to approximate the classical particle filter (PF). They adopt different strategies to alleviate filter degeneracy. LPF and LNETF localize observational impact but use different localization functions. They assimilate observations in a partially sequential and a simultaneous manner, respectively. In addition, LPF applies the resampling step, whereas LNETF applies the deterministic square root transformation to update particles. Both methods preserve the pos

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Qiao, Yu Kun, Qi Zhang, and Jin Sheng Zhang. "A Fault Predication Algorithm Based on Artificial Immune Particle Filter." Applied Mechanics and Materials 44-47 (December 2010): 3459–63. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.3459.

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Degeneracy problem is an inevitable result of sequential importance re-sampling (SIR) particle filter, and a mass of degenerated particles will influence the tracking ability of particle filter seriously. As a result, SIR particle filter based predication algorithm can’t predict system faults accurately. Artificial immune algorithm is characterized by a global ability to search for optimum, so it is introduced into the particle filter, named artificial immune particle filter (AIPF). Particles are regarded as antibodies in AIPF and particles with large weight aberrance and are cloned, and then

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Thaysen, Clara, Keenan Munno, Ludovic Hermabessiere, and Chelsea M. Rochman. "Towards Raman Automation for Microplastics: Developing Strategies for Particle Adhesion and Filter Subsampling." Applied Spectroscopy 74, no. 9 (2020): 976–88. http://dx.doi.org/10.1177/0003702820922900.

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Automation and subsampling have been proposed as solutions to reduce the time required to quantify and characterize microplastics in samples using spectroscopy. However, there are methodological dilemmas associated with automation that are preventing its widespread implementation including ensuring particles stay adhered to the filter during filter mapping and developing an appropriate subsampling strategy to reduce the time needed for analysis. We provide a solution to the particle adherence issue by applying Skin Tac, a non-polymeric permeable adhesive that allows microplastic particles to a

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Xue, Li, Chunning Na, and Yulan Han. "Improved Auxiliary Particle Filter for SINS/SAR Navigation." Mathematical Problems in Engineering 2021 (January 31, 2021): 1–9. http://dx.doi.org/10.1155/2021/6635390.

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In order to obtain the relatively appropriate importance density function and alleviate the problem of particle degradation, a new improved auxiliary particle filter algorithm is proposed. After calculating the auxiliary variable, the adaptive regulator is employed to obtain the state estimation. So, the latest measurement information is efficiently utilized to establish a better importance density function in the importance sampling process. Then, the process of particle weights’ adaptive adjustment and random-weighted calculation can keep the diversity of particles and improve the filter pre

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Guo, Yuyang, Xiangbo Xu, and Miaoxin Ji. "A Zero-Velocity Update Method for Adaptive Particle Filtering." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 38, no. 2 (2020): 427–33. http://dx.doi.org/10.1051/jnwpu/20203820427.

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Aiming at the low precision of Kalman filter in dealing with non-linear and non-Gaussian models and the serious particle degradation in standard particle filter, a zero-velocity correction algorithm of adaptive particle filter is proposed in this paper. In order to improve the efficiency of resampling, the adaptive threshold is combined with particle filter. In the process of resampling, the degradation co-efficient is introduced to judge the degree of particle degradation, and the particles are re-sampled to ensure the diversity of particles. In order to verify the effectiveness and feasibili

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Hoteit, Ibrahim, Xiaodong Luo, and Dinh-Tuan Pham. "Particle Kalman Filtering: A Nonlinear Bayesian Framework for Ensemble Kalman Filters." Monthly Weather Review 140, no. 2 (2012): 528–42. http://dx.doi.org/10.1175/2011mwr3640.1.

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This paper investigates an approximation scheme of the optimal nonlinear Bayesian filter based on the Gaussian mixture representation of the state probability distribution function. The resulting filter is similar to the particle filter, but is different from it in that the standard weight-type correction in the particle filter is complemented by the Kalman-type correction with the associated covariance matrices in the Gaussian mixture. The authors show that this filter is an algorithm in between the Kalman filter and the particle filter, and therefore is referred to as the particle Kalman fil

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Cong-An, Xu, Xu Congqi, Dong Yunlong, Xiong Wei, Chai Yong, and Li Tianmei. "A Novel Sequential Monte Carlo-Probability Hypothesis Density Filter for Particle Impoverishment Problem." Journal of Computational and Theoretical Nanoscience 13, no. 10 (2016): 6872–77. http://dx.doi.org/10.1166/jctn.2016.5640.

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As a typical implementation of the probability hypothesis density (PHD) filter, sequential Monte Carlo PHD (SMC-PHD) is widely employed in highly nonlinear systems. However, diversity loss of particles introduced by the resampling step, which can be called particle impoverishment problem, may lead to performance degradation and restrain the use of SMC-PHD filter in practical applications. In this paper, a novel SMC-PHD filter based on particle compensation is proposed to solve the problem. Firstly, based on an analysis of the particle impoverishment problem, a new particle compensatory method

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Murata, Masaya, and Kaoru Hiramatsu. "On Ensemble Kalman Filter, Particle Filter, and Gaussian Particle Filter." Transactions of the Institute of Systems, Control and Information Engineers 29, no. 10 (2016): 448–62. http://dx.doi.org/10.5687/iscie.29.448.

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44

Puderbach, Vanessa, Kilian Schmidt, and Sergiy Antonyuk. "A Coupled CFD-DEM Model for Resolved Simulation of Filter Cake Formation during Solid-Liquid Separation." Processes 9, no. 5 (2021): 826. http://dx.doi.org/10.3390/pr9050826.

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Abstract (sommario):

In cake filtration processes, where particles in a suspension are separated by forming a filter cake on the filter medium, the resistances of filter cake and filter medium cause a specific pressure drop which consequently defines the process energy effort. The micromechanics of the filter cake formation (interactions between particles, fluid, other particles and filter medium) must be considered to describe pore clogging, filter cake growth and consolidation correctly. A precise 3D modeling approach to describe these effects is the resolved coupling of the Computational Fluid Dynamics with the

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Poterjoy, Jonathan. "A Localized Particle Filter for High-Dimensional Nonlinear Systems." Monthly Weather Review 144, no. 1 (2015): 59–76. http://dx.doi.org/10.1175/mwr-d-15-0163.1.

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Abstract This paper presents a new data assimilation approach based on the particle filter (PF) that has potential for nonlinear/non-Gaussian applications in geoscience. Particle filters provide a Monte Carlo approximation of a system’s probability density, while making no assumptions regarding the underlying error distribution. The proposed method is similar to the PF in that particles—also referred to as ensemble members—are weighted based on the likelihood of observations in order to approximate posterior probabilities of the system state. The new approach, denoted the local PF, extends the

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Lee, J. J., J. H. Im, R. BenAim, et al. "Better understanding of the filtration characteristics in the flexible fibre filter module (3FM)." Water Science and Technology 55, no. 1-2 (2007): 77–83. http://dx.doi.org/10.2166/wst.2007.049.

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This study is about the particle retention and filtration characteristics of fibre filter. Four laboratory scale fibre filters with different heights were used in parallel at various packing densities and filtration velocities. Of all of the operating parameters studied, filtration velocity had the most influence. Contrary to general theories, pressure drop increases slightly during the filtration in spite of the continuous retention of particles. This may have occurred because of large porosity of the packing (about 93%). This might be considered an advantage of the filter and something that

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Siradjuddin, Indah Agustien, and Muhammad Rahmat Widyanto. "Particle Filter with Gaussian Weighting for Vehicle Tracking." Journal of Advanced Computational Intelligence and Intelligent Informatics 15, no. 6 (2011): 681–86. http://dx.doi.org/10.20965/jaciii.2011.p0681.

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To track vehicle motion in data video, particle filter with Gaussian weighting is proposed. This method consists of four main stages. First, particles are generated to predict target’s location. Second, certain particles are searched and these particles are used to build Gaussian distribution. Third, weight of all particles is calculated based on Gaussian distribution. Fourth, particles are updated based on each weight. The proposed method could reduce computational time of tracking compared to that of conventional method of particle filter, since the proposed method does not have to calculate

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Chan, Tak W., Marie Lee, Gary Mallach, and David Buote. "Efficiency of the Vehicle Cabin Air Filters for Removing Black Carbon Particles and BTEX from the Air Intake." Applied Sciences 11, no. 19 (2021): 9048. http://dx.doi.org/10.3390/app11199048.

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Abstract (sommario):

A laboratory study was conducted to evaluate 11 vehicular cabin filters (including electrostatic filters) in removing fine particles. Two filters with charcoal were also evaluated to understand their usefulness in removing five common volatile organic compounds, including benzene, toluene, ethylbenzene, and xylene isomers (BTEX). Filters were found to show considerably different particle filtration efficiencies (FE). Electrostatic filters were found to provide 20–60% better FE across all particle diameters (6–520 nm). For 6 nm particles, FE from 78 to 94% were observed (from the worst to the b

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Wang, Yang, Xiaoping Du, Ruixin Gou, Zhengjun Liu, and Hang Chen. "A Secondary Particle Filter Photometric Data Inversion Method of Space Object Characteristics." Electronics 12, no. 9 (2023): 2044. http://dx.doi.org/10.3390/electronics12092044.

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Abstract (sommario):

A secondary particle filter (SPF) inversion method for geostationary space object characteristics based on ground photometric data is presented. The method combines the estimation results of the standard particle filter (PF) algorithm and the resampling algorithm of the particle generation process. SPF first generates N particles according to the standard PF process, and performs the standard PF without resampling. Particle weight is an important indicator to determine the closeness of particles to the real state. With the progress of PF, the weight of particles closer to the real state will g

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Beskos, Alexandros, Dan Crisan, Ajay Jasra, Kengo Kamatani, and Yan Zhou. "A stable particle filter for a class of high-dimensional state-space models." Advances in Applied Probability 49, no. 1 (2017): 24–48. http://dx.doi.org/10.1017/apr.2016.77.

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Abstract We consider the numerical approximation of the filtering problem in high dimensions, that is, when the hidden state lies in ℝd with large d. For low-dimensional problems, one of the most popular numerical procedures for consistent inference is the class of approximations termed particle filters or sequential Monte Carlo methods. However, in high dimensions, standard particle filters (e.g. the bootstrap particle filter) can have a cost that is exponential in d for the algorithm to be stable in an appropriate sense. We develop a new particle filter, called the space‒time particle filter

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