323 results about "Particle number" patented technology

The invention discloses a FastSLAM algorithm based on an improved resampling method and particle selection. The algorithm comprises the following steps: (1) a robot predicts robot poses according to input control data and updates the robot poses and road signs according to measuring data combined with a measuring model of an external sensor of the robot; (2) the robot poses are predicted by the calculation of a particle filter, and a particle resampling criterion is amended according to an effective particle number, particle weighting covariance and particle-measuring residual consistency; (3) new particles are generated by using an index grad method and a crossover operator; (4) the robot is positioned, and a map is created according to the generated new particles. The invention improves the particle resampling criterion and a new particle-generating method in the FastSLAM algorithm, thereby obviously improving the estimation consistency of the FastSLAM algorithm to the robot poses and simultaneously improving the precision of the robot positioning and map creation.

The invention discloses an inhalable dust concentration measuring sensor, comprising: a semiconductor laser light source. An aspherical mirror, an incidence diaphragm, an extinction diaphragm, a photosensitive area, a spherical reflecting mirror, an emergent diaphragm and a light trap are arranged in turn in the forward direction of the beam. The extinction diaphragm is of a long tube shape, and the opening of the diaphragm is close to the photosensitive area; the spherical reflecting mirror located at the right side of the extinction diaphragm ensures that the photosensitive area and the photosensitive surface of a photoelectric detector are respectively located at the two sides near the spherical center of the spherical reflecting mirror and the physical image relation in geometrical optics is met; the photoelectric detector is a high-sensitivity photoelectric diode; and the sampling nozzles in the gas path are distributed with respect to the photosensitive area. In the invention, the measurement is more accurate as the quality concentration of the inhalable dust is calculated by the energy sum of scattered lights in the particle swarm, and the measuring sensor has wide application as being free from the limit of the total particle number in a unit volume; the signal-to-noise ratio of the sensor is greatly improved as the light path is provided with three diaphragms; and the noise is low, and the measurement is more accurate and stable as the concentration measuring circuit adopts an integral method.

The invention relates to a novel real-time PM2.5 (particulate matter 2.5) mass concentration monitoring device and a monitoring method. The monitoring device comprises a PM2.5 sampling mechanism, a particle aggregating mechanism and a photoelectric measuring mechanism, wherein the PM2.5 sampling mechanism is used for obtaining sample gas which only contains the PM2.5; the particle aggregating mechanism is used for aggregating particles entering the mechanism, absorbing minuteness particle ingredients and reducing the particle number; and the photoelectric measuring mechanism is used for converting an optical signal into a digital signal and processing so as to output the mass concentration data of the detected PM2.5 in real time. By utilizing the novel real-time PM2.5 (particulate matter2.5) mass concentration monitoring device and the monitoring method provided by the invention, the PM2.5 is subjected to aggregation treatment, so that the number of the particles in the sample air is greatly reduced, the data processing quantity of the device is reduced, and the measurement speed is accelerated; and in the photoelectric measurement procedure, peak value signals of large particles and signals of small particles are separately processed, and the signals are subjected to sublevel so as to calculate the average value, so that the precision of the device is improved, and thus the PM2.5 mass concentration is monitored efficiently in real time.

The invention discloses an asphalt mixture fatigue test numerical simulation method based on random generation. The method comprises the steps of randomly generating a test piece; determining the particle number, grading and irregular shape of coarse aggregates according to the test piece to be formed; determining that the coarse aggregates are not overlapped; generating irregular coarse aggregates; determining the minimum discrete unit size of bituminous mortar; filling the bituminous mortar; determining bituminous mortar grading and the dosage of asphalt in bituminous mortar according to the grading of an asphalt mixture; acquiring relative material parameters according to a bituminous mortar creep test and a spitting test; determining void ratio and void distribution and generating voids; conducting fatigue test numerical simulation; determining a virtual loading mode; conducting loading with a servo mechanism; conducting fatigue failure judgment. Through random test piece generation, three-dimensional configuration reconstruction of the asphalt mixture is achieved. By the adoption of the method, three-dimensional reconstruction of various grading levels, various void ratios and various asphalt mixtures can be achieved, and digital test piece reconstruction efficiency and accuracy are improved greatly.

A multilayer ceramic capacitor having internal electrode layers and dielectric layers, wherein a thickness of said dielectric layer is 2.0 μm or less, and an average particle number per one dielectric layer obtained by dividing the thickness of said dielectric layer by an average particle diameter of dielectric particles composing said dielectric layer is 3 or more and 6 or less.

The invention relates to a gasoline car particle capturing catalyst and a preparation method of the gasoline car particle capturing catalyst. The gasoline car particle capturing catalyst is characterized in that a first coating layer is coated on an inner framework arranged at the air inlet end of a carrier, a second coating layer is coated on an inner framework arranged at the air outlet end of the carrier, the height of the first coating layer and the height of the second coating layer are 50 to 100 percent of the height of the carrier, the coating amount of the first coating layer and the coating amount of the second coating layer are both 10 to 90 g/L, precious metal Rh is loaded in the first coating layer, the load amount of the precious metal Rh is 0.75 to 9.1 g/ft<3>, precious metal Pd and precious metal Rh are loaded in the second coating layer, the load amount of the precious metal Rh is 0.09 to 2.5 g/ft<3>, and the load amount of the precious metal Pd is 5 to 50 g/ft<3>. The preparation method disclosed by the invention is simple, the prepared gasoline car particle capturing catalyst is capable of well reducing the PN (Particle Number), and a single Rh coating layer is arranged at the air inlet end, so that the generation of palladium-rhodium alloy is avoided; meanwhile, less precious metal Rh is introduced into a Pd coating layer arranged at the air outlet end, so that the oxygen storage ability of the coating layer can be increased; meanwhile, high activity and high temperature aging resistance of the gasoline car particle capturing catalyst are also ensured, and the nitric oxide (NOx) treatment ability of the gasoline car particle capturing catalyst is increased.

For analyzing a sample containing particles of at least two categories, such as a sample containing blood cells, a particle counter subject to a detection limit is coupled with an analyzer capable of discerning particle number ratios, such as a visual analyzer, and a processor. A first category of particles can be present beyond detection range limits while a second category of particles is present within respective detection range limits. The concentration of the second category of particles is determined by the particle counter. A ratio of counts of the first category to the second category is determined on the analyzer. The concentration of particles in the first category is calculated on the processor based on the ratio and the count or concentration of particles in the second category.

An LED comprises a substrate, an LED chip mounted on the substrate, an encapsulation encapsulating the LED chip, and a phosphor layer containing phosphor particles disposed on an outer surface of the encapsulation. A luminous intensity I of light generated by the LED chip and a radiation angle θ are in Lambertian distribution and satisfy following formula: I=I₀×cos θ, here the radiation angle θ is not lower than 0°, and is not higher than 90°, and I₀ is a luminous intensity at a central axis of the LED chip, and the radiation angle θ is an angle between the light and the central axis. One of parameters of concentration, particle number of the phosphor particles in the phosphor layer and a thickness of the phosphor layer is also in Lambertian distribution relative to the radiation angle θ.

The invention relates to a method for automatically classifying particles and belongs to a particle classification method. The method comprises the following steps of: obtaining at least two types of characteristic information through collecting scattered light signals of a particle detector and respectively mapping the at least two types of the characteristic information of the particles into a two-dimensional scatter diagram; carrying out Gaussian filtering on the two-dimensional scatter diagram and selecting a peak value of the Gaussian filtering as an initial value of means clustering; clustering data of the two-dimensional scatter diagram by using the means clustering; and calculating the particle number of each area according to clustered results, so as to count percentage of the particle number of each area. According to the invention, the boundary position, shape, direction and size of each area can be adjusted; and the method provided by the invention is strong in accuracy and stability, and can be used for improving the adaptability of the scatter diagram to various samples.

The invention relates to a method of particle filtering based on multi-suggesting distribution, which belongs to fields of signal processing, artificial intelligence and machine vision. The invention uses various suggesting distribution in the frame of particle filter: checking, firstly, probability distribution, extended Kalman filter, unscented Kalman filter etc., treating a sample particle using dividing and conquering sampling strategy, dividing total particle numbers into a plurality of portions, extracted from different suggesting distribution respectively. To this end, the run time of particle filter can reduced and the operating efficiency is able to be improved, while the estimated precision of particle filter can not be lost. User may carry out parameter arrangement according to the demand for time and precision. The invention has extensive application prospect in the field which relates to nonlinear filtering problem.

A semiconductor cleaning apparatus according to the present invention comprises: a particle monitor which measures the number of particles in a processing liquid used in a rinse process after a semiconductor wafer is subjected to a cleaning process by means of the processing liquid; a specific resistance measuring unit which measures a specific resistance of a processing liquid used in the rinse process; and a control unit which determines an end point at which the rinse process is completed on the basis of the number of particles measured by the particle monitor and the specific resistance measured by the specific resistance measuring unit to end the rinse process.

The invention relates to a likelihood-function-particle-filter-based power battery state-of-charge (SOC) estimation method and system. A state equation and a measurement equation are obtained by a battery Thevenin model; after parameter initialization, state prediction is carried out and a mean value and a covariance of a state prediction value are calculated; and sampling is carried out again and a sampling distribution function is reconstructed. A voltage prediction value of a battery end is calculated, a particle weight is calculated, weight normalization is carried out, and an effective particle number is calculated. The effective particle number Neff is compared with an effective particle number threshold value; when the Neff is less than Nthr, a Laplacian distribution is used as a likelihood function and a variance regulatory factor and a working condition adaptation factor are introduced, thereby modifying a variance of the likelihood function in an adaptive mode and thus realizing adaptation to different working conditions of the power battery. And then an updated SOC estimation value and covariance are obtained finally. According to the system, a microcontroller is connected with a voltage sensor and a current sensor; and all program execution modules are arranged in the microcontroller. According to the invention, the effective particle number is increased; overcorrection of the variance is effectively avoided; and the estimation precision is high.

The invention relates to a strap-down inertial navigation system large azimuth misalignment angle initial alignment method based on MRUPF (Multi-resolution Unscented Particle Filter), comprising the following steps of: firstly, establishing a state space model for the initial alignment of a strap-down inertial navigation system static substrate under the large azimuth misalignment angle condition to carry out filtering initialization; then carrying out the state estimation of the initial alignment by utilizing a UPF filtering algorithm; selecting particles and particle weights by utilizing a multi-resolution method at a moment to reduce the number of the particles; and continuing to carry out the state estimation of the initial alignment by utilizing the UPF filtering method by taking the selected particle set and the particle weights as initial particle sets and the weights to obtain a misalignment angle estimated value. In the invention, the UPF particle number is reduced through the multi-resolution method, thereby reducing the calculated amount, and the real-time performance of the initial alignment of the strap-down inertial navigation system under a large azimuth misalignment angle is improved while the initial alignment accuracy is ensured. The invention is suitable for the initial alignment of the strap-down inertial navigation system.

The invention discloses a method and device for detecting indoor heavy metal pollution by single-particle aerosol mass spectrometry. The method is as follows: firstly, a polystyrene ball is used to perform a particle size calibration experiment on the instrument, and then a standard solution of known metal ions is used Carry out the mass number correction experiment. After the calibration is completed, use SPAMS to collect indoor atmospheric aerosols in different areas and heights in real time, and then use SPAMS to analyze and collect various parameters and status information of heavy metal particles in the samples in real time. The SPAMS in the device includes a sequentially connected sampling module, a particle size measurement module, an ionization source module, a mass analyzer module, a data acquisition module and a data analysis module. The invention can quickly, sensitively, accurately and real-time online detect the particle number concentration, particle size distribution, mass spectrum characteristics, mixing state, etc. of indoor heavy metal particles, and judge its possible source.

The invention provides an unscented particle filtering method based on a particle swarm optimization algorithm, which comprises the steps of: 1, initial time: obtaining a group of initial particles from an initial distribution p(x0), setting an initial average and variance of the group of initial particles; 2, sampling sequential importance; 3, updating weight; 4, obtaining an normalized weight; 5, sampling; 6, updating state; and 7, solving a globally optimum solution G(t) at the current time. The invention ensures that a particle swarm more trends to a high likelihood region before the weight is updated through a particle swarm optimization process, thereby solving the problem of sample depletion to a certain degree. The optimization process ensures particles far away from real state trends to an area with high occurrence probability of the real state, thereby improving the action effect of each particle. Compared with other intelligent optimization algorithms, the particle swarm optimization algorithm has the advantages of easy implementation and no adjustment on various parameters, lowers the particle number required by accurate estimation, and improves the computing efficiency of filtering.

The present invention discloses a mobile surveillance car-based single particle aerosol online mass spectrum detection method, which is based on a particle online mass spectrum detection system, the system includes a single particle aerosol online mass spectrometer and a mobile surveillance car, the single particle aerosol online mass spectrometer is arranged on the mobile surveillance car, pollution source particles can be directly detected on line by car- mounted single particle aerosol online flight time mass spectrum to obtain particle number concentration, particle diameter spectrum and particulate online mass spectrometry data; by use of ART-2a approach, particle components are classified to obtain single particle chemical composition data under different time resolution and different particle diameters; mass spectrometry direct analytical technique is used for analysis of particle sources for determination of the particle sources. Single particle diameter and chemical composition information can be detected simultaneously, a sample can be directly and quickly detected without sample preprocessing, high throughput sample analysis can be achieved, and source analysis can be achieved.

A laminated arc heater high-enthalpy airflow parameter diagnosis system is used for obtaining the airflow parameters (particle number density and static temperature) of a high temperature flow field in the ground heat protection test of an arc heater, and online diagnosing high temperature disassociated air test airflow in the arc heater by using an atom O (777.19 nm) spectral line to obtain the plasma airflow temperature and the atom oxygen particle number density in the arc heater. The system can be used as a routine way for the arc heater high-enthalpy airflow parameter diagnosis.

The invention discloses a method and a device for tracking a region of interest in a video. The method for tracking the region of interest in the video comprises the steps: first, obtaining motion vectors of pixels or macro blocks in an existing frame, confirming distributed parameters of the movement speed of the region of interest (ROI) according to the motion vectors, confirming ROI scaling parameters according to the ROI state in a reference frame, utilizing the distributed parameters of the movement speed of the ROI and the scaling parameters to perform state transition to particles obtained through sampling in the existing frame, and confirming the ROI position and the ROI size of the existing frame according to the particles after the state transition. The method and a device for tracking the region of interest in the video can utilize motion vector information which exists in compressed code flows or is generated in encoding to guide the state transition process of the particles, accordingly can decrease required particle number in the tracking process under the condition that the tracking effect is ensured, further reduce the complexity level of tracking processing, and can have good tracking effect.

The invention discloses a construction method for a two-dimensional discrete element model of a mother rock and a particle material thereof. The construction method comprises three steps of grading curve correction, mother rock test discrete element modeling and particle material discrete element modeling. The step of grading curve correction comprises the sub-step of redistributing the mass of a smallest particle fraction to the remaining particle fractions according to the quality ratio of particles of particle fractions except the particle fraction of a finest stage in a grading curve to obtain a correction simulation curve in a computer operation simulation range and a particle diameter range of basic particle units. The particle material discrete element modeling comprises the sub-step of: firstly, randomly generating a rock area outline; secondly, forming a rock unit from the basic particle units; thirdly, assigning contact attributes in rocks; finally, assigning the contact attributes between the rocks. In rock aggregation generated according to the construction method, good randomness and diversity are available for the particle number and the form of composed rocks and the actual outline of the rocks; the rock size is generated according to a certain grading condition and satisfies the requirement of certain porosities.