508 results about "Particle Size Analyzer" patented technology

The invention relates to the technical field of dust fall control, in particular to a mining spray dust fall control method and system based on image recognition, and the method comprises the steps: determining a corresponding simulation mining area model based on the mining area parameters of a to-be-controlled mining area when an actual dust diffusion diagram contains a shadow region; based on the construction parameters of the to-be-controlled mining area and the simulated mining area model, a simulated dust diffusion diagram corresponding to the to-be-controlled mining area is obtained; determining a target dust diffusion diagram based on the actual dust diffusion diagram and the simulated dust diffusion diagram; edge detection and granularity analysis are carried out on the target dust diffusion diagram, and dust information corresponding to the to-be-controlled mining area is determined from the target dust diffusion diagram; and generating a spraying regulation instruction based on the dust information, wherein the spraying regulation instruction is used for controlling the spraying equipment to perform dust falling operation based on the spraying regulation instruction. The accuracy of a dust detection result is conveniently improved, so that the dust falling effect is improved.

The invention discloses an optimized preparation method of a high-strength flame-retardant polyamide-based composite material in the technical field of information, which comprises the following steps: in the preparation process of the composite material, acquiring online dispersed state monitoring data of a modified filler by using a laser particle size analyzer and an optical microscope, including particle size distribution, agglomeration degree and dispersion uniformity of the filler; according to online dispersion state monitoring data, parameter ranges of melt flow property characterization are determined, the parameter ranges comprise the shearing rate and the temperature, particle size distribution data are used for determining the shearing rate range, small particle size distribution corresponds to the high shearing rate range, and agglomeration degree data are used for determining the temperature range; the higher degree of agglomeration corresponds to a higher temperature range to promote the dispersion of the filler, and these parameters are directly used to guide the setting of the subsequent rheological test.

The invention provides an intelligent control method and system for a lithium carbonate preparation process, and the method comprises the steps: collecting the temperature field, ion concentration, feeding flow velocity and turbulence intensity data of a reaction kettle through a sensor array, and generating a state feature vector through multivariate analysis; inputting the feature vector into a depth prediction model to output a particle size distribution probability cloud picture and an impurity trend; inputting the probability cloud picture and the impurity trend into a multi-target optimizer to generate a temperature compensation value, a feeding correction coefficient and a stirring adjustment instruction; inputting the instruction into an anti-interference execution module and converting the instruction into an equipment driving signal; actual crystal data are obtained through an online particle size analyzer, and the prediction model is updated; and outputting a closed-loop optimization instruction to the execution terminal through the digital twin platform. The product consistency and the production stability are synchronously improved through full-process closed-loop intelligent control, and reliable technical support is provided for continuous production of battery-grade lithium carbonate.

The invention discloses an SEM image granularity analysis method and system based on a visual large model, and relates to the technical field of image recognition. The method comprises the steps that an SEM image is acquired, automatic scale identification is performed on the SEM image, and the actual length and the pixel length of the scale and the actual length of each pixel are obtained; an SEM image set containing particle features is collected, particles in the SEM image set are labeled, and an SEM image training set and an SEM image test set are constructed based on a labeling result; constructing a visual large model, and performing fine tuning on the visual large model by using the SEM image training set; reasoning the SEM image test set by using the fine-tuned visual large model to obtain a particle segmentation result; attributes of each segmented particle are calculated based on the actual length of each pixel for particle size analysis. According to the scheme, the efficiency, precision and consistency of particle analysis are improved, and the efficient and accurate analysis requirements of microscopic particles are met.

The invention discloses an electrical grade magnesium oxide uniformity detection system, and relates to the technical field of magnesium oxide uniformity detection, the electrical grade magnesium oxide uniformity detection system comprises a workbench, a support plate and a laser particle size analyzer body, a connecting shaft is rotatably arranged on the top surface of the workbench, a gear is fixedly connected to the bottom of the connecting shaft, a connecting plate is fixedly connected to the top of the connecting shaft, and a placing mechanism is arranged on the side surface of the connecting plate; an electric push rod is arranged on the inner top face of the workbench, and a driving mechanism is arranged at the movable end of the electric push rod. When a short cylinder moves in a return groove, a placement box can move left and right to flatten electrical-grade magnesium oxide particles in the placement box, so that electrical-grade magnesium oxide detection is facilitated; and when the short cylinder moves in the straight groove, the placement box can be conveniently fixed, so that the placement box is ensured to be positioned under the laser particle size analyzer body, and the electrical-grade magnesium oxide particles can be further conveniently detected.

The invention relates to the technical field of high-performance structural ceramic materials and corrosion resistance optimization thereof, in particular to a preparation method of high-performance silicon nitride ceramic, which realizes performance improvement through dynamic optimization of a composite sintering aid, closed-loop regulation and control of air pressure sintering and multi-process data linkage. In the raw material pretreatment stage, a laser particle size analyzer is adopted for monitoring particle size distribution in real time, surface modification parameters are adjusted in a linkage mode, and a uniform monomolecular coating layer is formed; the proportion of rare earth oxide and aluminum oxide in the composite sintering aid is dynamically adjusted according to the fluctuation of the mixing torque, and agglomeration and segregation of the aid are inhibited. And in the air pressure sintering stage, the argon pressure and the heating rate are dynamically adjusted based on the slope of a shrinkage curve, and directional arrangement of beta-phase grains is promoted by combining low-temperature nitrogen protection and high-temperature argon densification. And multi-dimensional process control synergistically optimizes grain boundary components, structure and density, so that the corrosion resistance and the service life of the silicon nitride ceramic in a sulfur-containing environment are remarkably improved and the service life of the silicon nitride ceramic in the sulfur-containing environment is remarkably prolonged.

In one embodiment, the disclosure provides a method on a drilling fluid. The method may include acquiring data from each of a particle-size analyzer, x-ray fluorescence instrument, a mud check, and optionally an x-ray diffraction instrument, to yield acquired data for each of a plurality of drilling mud samples, wherein: (a) the particle size analyzer measures a plurality of drilling mud samples; (b) the x-ray fluorescence instrument and the x-ray diffraction instrument measure a mineral analysis of the plurality of drilling mud samples; and (c) the mud check measures properties of the plurality of drilling mud samples. Further, the method may include plotting a particle size distribution curve for at least one of the plurality of drilling mud samples, and calculating an amount of abrasive formation material(s) within at least one of the plurality of drilling mud samples. Further still, the method may include adjusting the drilling fluid.

The invention relates to the technical field of laser particle size analyzers, in particular to a laser particle size analyzer with a double-ultrasonic structure, which comprises a particle size analyzer body, a sample pool is arranged on the particle size analyzer body, a sample dispersion mechanism for crushing particle blocks is arranged in the sample pool, and a stirring auxiliary mechanism for preventing suspended particles from settling is arranged above the sample pool. The stirring auxiliary mechanism can push the particles to a sound field strong area of the sample dispersion mechanism so as to improve the dispersion efficiency, and a splash-proof covering mechanism is arranged at the upper end of the sample pool. By arranging the sample dispersion mechanism and adopting a mode of combining phase orthogonality and material orthogonality layout, a stable three-dimensional acoustic vortex can be formed in the sample pool, and the coverage range of the ultrasonic cavitation effect can be obviously improved, so that the particle dispersion uniformity is improved, and the particle dispersion efficiency is improved. A detachable low-frequency ultrasonic vibrator is adopted at the bottom, so that the penetrating power of a high-concentration and high-viscosity sample is further enhanced, and dispersion dead angles can be effectively eliminated.

The invention belongs to the technical field of image processing, and particularly relates to an ore grinding and screening monitoring method and system based on image particle size analysis, and the method comprises the steps: collecting an ore image, generating a distance transformation diagram, and constructing an extreme value topology network; calculating the relative topology significance of adjacent maximum value points, and constructing a peak-valley independence index in combination with the spatial distance; performing iterative fusion on the maximum value points based on the peak-valley independence index to obtain a final mark set; and performing watershed segmentation by taking the final mark set as a seed, calculating ore particle size cumulative distribution, extracting a characteristic particle size index, and adjusting grinding process parameters according to the characteristic particle size index. Through the combined constraint of the relative topology saliency and the peak valley independence index, the method can adapt to multi-scale features and effectively eliminate the interference of the surface texture of the ore, solves the problem of over-segmentation caused by rough surface in the traditional method, and realizes the real-time optimization, energy conservation and consumption reduction in the grinding process.

The invention relates to a preparation method of a high-thermal-conductivity hexagonal boron nitride film in the technical field of new materials, which comprises the following steps: acquiring particle size distribution data of hexagonal boron nitride powder treated by silane, and measuring the distribution condition of hexagonal boron nitride particles with different particle sizes by a particle size analyzer to obtain a particle size distribution curve; the influence of key process parameters on the heat-conducting property, the mechanical strength and the flame-retardant property is verified through experiments, performance data under different process parameters are obtained, and the influence rule of silanization treatment conditions on the surface property of hexagonal boron nitride and the performance of the composite material is focused on; and according to the heat-conducting property, the mechanical strength and the flame-retardant property data, optimizing process parameters by adopting a particle swarm optimization algorithm in a multi-objective optimization algorithm to obtain an optimal process parameter combination.

The invention discloses a prospecting method and a prospecting system for mainly extracting soil micro-fine particles in a shallow coverage area, and the prospecting method comprises the following steps: separating a micro-fine particle part from a soil sample by adopting a wet screening method according to a preset particle size range to obtain a target micro-fine particle sample; the method comprises the following steps: for a target micro-fine particle sample, acquiring chemical component data through an X-ray fluorescence spectrophotometer, and determining the content and distribution characteristics of main elements in the sample; analyzing the mineral composition of the target micro-fine particle sample by adopting an X-ray diffractometer, and identifying the types and relative contents of main minerals in the sample; determining the particle size distribution of the target micro-fine particle sample through a laser particle size analyzer to obtain the proportion information of particles with different particle sizes in the sample; according to the geophysical data, gravity, magnetic force and electrical parameters of the target area are extracted, and a geophysical feature model is established; and carrying out data fusion on the geochemical features and the geophysical feature model, and extracting key feature variables in multi-source information by adopting a principal component analysis method.

The invention provides an ore particle granularity detection device and method based on a flexible vibration disk, and the device comprises the flexible vibration disk which is used for vibrating an ore material at a certain frequency and amplitude, so that the ore material is uniformly distributed and is in a proper posture; the image acquisition device is used for continuously shooting the ore materials on the flexible vibration disc to obtain ore images; the image processing device is used for carrying out preprocessing, segmentation, feature extraction and particle size analysis on the ore image and outputting the ore particle size distribution condition and an accumulative distribution curve; and the result output device is used for displaying the ore image and the granularity analysis result. According to the invention, while material accumulation is prevented, real-time, accurate and efficient detection of attitude distribution of ore materials is realized, and the method has the advantages of low cost of detection equipment, easy maintenance, strong interference resistance, high accuracy and stability of detection results, and the like.

The invention discloses high-purity quartz sand airflow crushing and ultra-fine refining equipment, and relates to the technical field of quartz sand refinement, the high-purity quartz sand airflow crushing and ultra-fine refining equipment comprises a mounting bottom plate, a controller is arranged at the top of the mounting bottom plate, and feeding equipment used for conveying quartz sand is arranged at the position, close to the center, of the top of the mounting bottom plate. According to the high-purity quartz sand airflow crushing and ultra-fine refining equipment, when high-purity quartz sand needs to be subjected to fine crushing, firstly, materials are conveyed into a primary crushing bin, the quartz sand is subjected to ultra-fine crushing through a plurality of first high-pressure nozzles, and when a laser particle size analyzer detects that the granularity of the crushed materials is large, the materials are conveyed into a secondary crushing bin through a plurality of second high-pressure nozzles; and a plurality of second high-pressure nozzles are moved upwards to the positions flush with the outer surfaces of a plurality of first high-pressure nozzles, the material crushing angle and strength are increased, and the problems that in the prior art, in the process that crushing equipment crushes high-purity quartz sand, the spraying angle and the coverage range of high-pressure airflow are relatively single, and the crushing efficiency is low are solved.

The invention provides an ore particle granularity detection device and method based on a flexible vibration disk, and the device comprises the flexible vibration disk which is used for vibrating an ore material at a certain frequency and amplitude, so that the ore material is uniformly distributed and is in a proper posture; the image acquisition device is used for continuously shooting the ore materials on the flexible vibration disc to obtain ore images; the image processing device is used for carrying out preprocessing, segmentation, feature extraction and particle size analysis on the ore image and outputting the ore particle size distribution condition and an accumulative distribution curve; and the result output device is used for displaying the ore image and the granularity analysis result. According to the invention, while material accumulation is prevented, real-time, accurate and efficient detection of attitude distribution of ore materials is realized, and the method has the advantages of low cost of detection equipment, easy maintenance, strong interference resistance, high accuracy and stability of detection results, and the like.

The invention relates to the technical field of control systems, and particularly discloses a crushed material drying system and an operation method thereof, and the crushed material drying system comprises a data acquisition module, a multi-source data fusion module, a dynamic shunting decision module, a cooperative control module and a tail gas treatment optimization module. The data acquisition module acquires particle size distribution, moisture content, stacking density and dust concentration data of materials in real time through a laser scattering type particle size analyzer and a microwave moisture sensor, and transmits the data to the multi-source data fusion module through a Modbus protocol; according to the operation method, through an abnormal working condition grading alarm mechanism, a genetic algorithm optimization fuzzy rule base and multi-module data linkage, the problems of local overheating and low energy efficiency caused by parameter mismatch in traditional control are solved, and global optimization of drying efficiency, energy consumption and operation stability is achieved.

The invention discloses a laser particle size detection system and a feeding device, and relates to the technical field of laser particle size analyzers. The system comprises a laser, a lens unit, a sample chamber, a photoelectric detection unit, an imaging unit, a sample introduction unit, a temperature control unit and an information interaction and processing unit. The feeding device comprises a shell, a motor, an annular water sprayer and the like. A sample is preliminarily dispersed by the feeding device, is further dispersed by the ultrasonic disperser and then enters the sample chamber. After the system is started, laser emitted by the laser device is processed and enters the sample chamber, generated diffraction light is received by the photoelectric detection unit, meanwhile, the thermotank and the thermodetector guarantee stable temperature, the water level induction meter monitors the water level, and the information interaction and processing unit processes data and transmits a result to the imaging unit to be displayed. Compared with the prior art, the method has the advantages that the detection precision, the operation convenience and the detection efficiency are improved, the stability and the repeatability are good, the particle size characteristics of the sample can be more accurately reflected, the detection time is shortened, and the operation difficulty is reduced.

The invention relates to the technical field of coal gangue magnetic separation, in particular to a coal gangue magnetization fluidized roasting device which comprises a raw material preprocessing module, a fluidized magnetization roasting module, a magnetic separation module, a data center module and a mass feed module. The raw material preprocessing module realizes gradient crushing and dynamic screening of coal gangue through a multi-stage crushing unit and a closed cycle pneumatic classification device, and the online particle size analysis device monitors particle size data in real time and transmits the particle size data to the data center module; the fluidization and magnetization roasting module adopts a double-cavity reaction tower structure, and is combined with an infrared thermal imager array and a PI (Proportional Integral) controller to regulate and control the mixing proportion of fluidization gas and inhibit the oxidation of ferric oxide; through multi-module data driving optimization, the technical problems of insufficient multi-variable coupling regulation, low separation precision and high energy consumption are solved, and low-carbon efficient resourceful treatment of the coal gangue is realized.

The invention relates to the technical field of grading gangue selection of coal gangue, in particular to a grading gangue selection method of coal gangue, which comprises the following steps: acquiring mineral texture data through a multispectral imaging device, analyzing the spatial distribution of aluminum and silicon elements in combination with an X-ray diffractometer, and generating a three-dimensional component map through spatial registration and fusion with infrared heat value data; impurities are dynamically removed through sulfur element spectrum detection, and the air pressure and the material flow of winnowing equipment are adjusted by matching roasting process parameters; components of the sorted waste are analyzed through an X-ray fluorescence spectrometer, particle size data are obtained through a laser particle analyzer, a genetic algorithm is input to iteratively optimize detection channel combination and sampling density, a resource distribution instruction is generated, and equipment parameter correction is fed back. According to the method, aluminum-silicon ratio critical value accurate identification, sorting parameter dynamic adaptation and waste recycling path optimization are realized, and the problem of overburning caused by insufficient quantitative analysis of element distribution in the prior art is solved.

The utility model provides a laser particle size analysis pretreatment device and battery slurry detection equipment, and belongs to the technical field of battery slurry stirring analysis. The laser particle size analysis pretreatment device comprises a stirring assembly and an ultrasonic assembly, wherein the stirring assembly comprises a first driving unit and a plurality of stirring rods connected with the first driving unit; the ultrasonic assembly comprises an ultrasonic transducer and a box body, the box body is provided with a containing cavity, a plurality of containers in one-to-one correspondence with the stirring rods are arranged in the containing cavity, the containers are used for containing slurry to be treated, and the ultrasonic transducer is used for applying ultrasonic vibration to the slurry in the containers; and the plurality of stirring rods are configured to synchronously rotate under the driving of the first driving unit so as to respectively stir the slurry in the corresponding containers. According to the structural design, multiple groups of samples can be automatically stirred and ultrasonically vibrated at the same time, the sample treatment efficiency can be improved, and the sample treatment consistency can also be improved.

The invention relates to the technical field of particle size analysis, solves the technical problem of signal distortion in rodlike abrasive dust particle size monitoring in a high-intensity magnetic field environment, and particularly relates to an inverse Fourier transform particle cross detection method and system for a laser particle analyzer, and the method comprises the following steps: collecting an original scattered light intensity signal and magnetic field intensity data; calculating a magnetic field change gradient based on the magnetic field intensity data; calculating a predicted phase offset used for eliminating signal distortion caused by rotating speed abrupt change by using the magnetic field change gradient; and identifying an oscillation risk period based on the magnetic field change gradient and a preset risk determination threshold. The method breaks through the hypothesis of a traditional Mie theory on spherical particles, establishes a scattering kernel function of the rod-shaped particles based on a T matrix theory, introduces a magnetic field coupling term, and quantifies the influence of a magnetic field on particle orientation and scattering signals. The situation that single particles are misjudged as multi-size mixed particles due to scattering double-peak artifacts caused by directional arrangement of the rod-shaped particles in a high-intensity magnetic field is avoided, and the particle size inversion precision is remarkably improved.

The invention provides a reverse particle size analysis method and system for a lithium ion battery, and the method comprises the steps: carrying out the detailed disassembly, cleaning, adhesion, stripping and high-temperature treatment of a to-be-analyzed cell, can accurately analyze the particle size distribution of an electrode active material in the positive and negative electrode materials of the lithium ion battery, guarantees the purity and activity of the electrode active material, and improves the detection accuracy. Therefore, the particle size analysis result is more accurate and reliable. According to the invention, the performance of the battery material is optimized, the safety of the battery is improved, the service life of the battery is prolonged, and important data support is provided for research, development and improvement of the battery material.

The invention discloses a dual-lens laser particle analyzer with an automatic calibration function. The dual-lens laser particle analyzer comprises a lead-in assembly, a shaking assembly and a mist brushing assembly, the introduction assembly is used for mixing and introducing to-be-measured particles and a water source, the shaking assembly is used for continuously shaking the particles of a to-be-measured mixed solution so as to ensure that the particles are uniformly dispersed, and the mist brushing assembly is used for brushing away mist which is generated on a lens due to too high humidity and interferes with the laser measurement degree. Through the combination of the first fixing plate, the first fixing shaft, the fixing ring and the torsional spring, the first sample pool can flexibly shake within a certain range, the motor drives the reciprocating lead screw to drive the toothed plate to move, the first sample pool can shake and swing, and through the continuous and diverse movement mode, the detection accuracy is improved. The uniform distribution of the particles in the solution is ensured, the interference of particle precipitation or aggregation on the measurement result is avoided, and the accuracy of measuring the particle size by the laser particle analyzer is obviously improved.

The invention relates to the technical field of molten salt treatment, and discloses a molten salt recovery system based on a steel belt cooling granulator. The system comprises a molten salt physical property monitoring module, a viscosity modeling module, a cooling optimization module, a partition temperature control module, a phase change monitoring module, a dynamic adjustment module, a particle size analysis module, a quality grading module, a pneumatic conveying module and a waste heat recovery module. The progressive crystallization control of the molten salt particles is realized; a heat pipe type heat exchanger and an organic Rankine cycle system are integrated at the waste heat recovery end, so that comprehensive energy consumption is reduced; the environment regulation and control end monitors the workshop temperature and humidity in real time based on a dew point calculation model, and the long-term stability of hygroscopic fused salt particles is guaranteed. According to the method, four technical bottlenecks of out-of-control crystallization, energy waste, classification loss and environmental interference in fused salt recovery are overcome, and low-cost, high-purity and zero-waste fused salt resource recycling is realized.

An adaptive flow regulation system for a tilting melting hearth atomization system includes: a load cell sensor configured to capture a weight of a molten metal within a tilting melting hearth during a pouring operation; a process camera configured to capture visual characteristics of the molten metal during the pouring operation; a particle size analyzer configured to analyze a metal powder following an atomization process to determine a particle size distribution of the metal particles; an actuator coupled to a linkage configured to support and move the tilting melting hearth to a desired hearth tilt angle; and a central processing unit (CPU) having a machine learning program configured to receive data from the load cell sensor, the process camera, and the particle size analyzer and to send a control signal to the actuator for controlling a pour rate from a melting cavity of the tilting melting hearth.

The invention relates to spraying equipment for preventing and controlling atmospheric pollution in the field of spraying devices, and through a plurality of nozzles mounted on a rotating ring and an inserting cylinder driven by an electric push rod, the nozzles are quickly replaced, the spray particle size is quickly and accurately adjusted, and the mode of manually replacing the nozzles is replaced; the spray particle size adjusting efficiency and accuracy are improved, the requirement of low-temperature weather for the fog drop particle size is met, fog drop icing is delayed, and the dust adsorption capacity of fog drops at the low temperature is improved; meanwhile, the spray particle size is detected in real time through a laser particle size instrument arranged on the front side of the air blowing cylinder, and when it is found that the spray particle size does not meet the requirement, early warning is given out in time to remind an operator to conduct maintenance, and waste of sedimentation liquid is reduced; in addition, by arranging a heating sleeve and a heat exchange pipe, the sedimentation liquid is preheated and heated in winter, the freezing speed of the fog drops is further delayed, the dust particle adsorption effect of the fog drops is improved, and energy is saved.

The preparation method comprises the following steps: selecting an abrasive material base material, mixing the abrasive material base material with a silane coupling agent for chemical modification, coating the surface with a modified abrasive material with a functional layer, adding the modified abrasive material into a stirring container, and dispersing to obtain the rough polishing liquid applied to the diamond substrate. An oxidizing agent and a dispersing agent are added into the abrasive dispersion liquid to be stirred to form a polishing solution, the particle size distribution condition of the modified abrasive in the polishing solution is monitored in real time through an online particle size analyzer, and the ultrasonic power and the treatment time are automatically adjusted; adding a pH regulator into the polishing solution by adopting a step-by-step titration method, and adjusting the pH value to 6-9; the polishing solution is filtered through a micro-filtration membrane, undispersed particles and impurities are removed, and a polishing solution finished product is obtained; through the chemical modification and ultrasonic-assisted technology and the real-time monitoring and automatic adjusting process, the dispersity of the grinding material and the uniformity of the polishing solution are remarkably improved, and the particle size distribution of the grinding material is optimized, so that the high-quality polishing solution is obtained.

The invention relates to the technical field of automatic control, in particular to a PE thermal insulation pipe production equipment control method and system.The method comprises the following steps that based on raw material particle size distribution characteristics, heating temperature control parameters are adjusted, the viscosity state is recognized in combination with screw torque and rotating speed, and the feeding rate of each section is adjusted according to the viscosity difference; forming uniformity is calculated and foaming agent injection parameters are adjusted in combination with a foam structure, and flow velocity parameters of a cooling area are adjusted in combination with thermal load evaluation. According to the invention, by introducing raw material particle size analysis parameters and combining torque and viscosity change characteristics, the heating temperature control and extrusion viscosity adjustment process is optimized, the adaptability of equipment to material physical property change is enhanced, the foaming agent injection process is fed back by using foam structure distribution, the foaming uniformity and injection accuracy are improved, and the foaming efficiency is improved. And by adopting linkage analysis of heat release intensity and cooling rate, dynamic regulation and control of the cooling circulation rate are realized, and the consistency and stability of cooling shaping are improved.

The utility model relates to the technical field of powder metallurgy, in particular to a superfine tungsten powder reduction rotary furnace which mainly comprises a furnace body, a heating wire, a support, a furnace tube component and a detection component. The design of the spiral lifting plate is optimized in different reaction stages, the reduction efficiency is improved, the oxygen content of the tungsten powder is reduced, the spiral lifting plate is not arranged in the cooling section, the rotation resistance is reduced, then the power consumption of the motor is reduced, the tungsten powder is cooled by arranging reverse hydrogen, the reverse hydrogen is heated and transmitted to the deoxidation section, and the oxygen content of the tungsten powder is reduced. The energy is further saved, the tungsten powder is prevented from growing up, the laser particle size analyzer is arranged to detect the particle size of the tungsten powder in real time, the process is rapidly adjusted, quality deviation is avoided, the recovery rate of the tungsten powder is improved, and the situations that the powder particle size distribution is wide and deoxidation is not thorough are avoided.

A system self-calibration method for testing granularity of spherical ammonium perchlorate by a dynamic image method relates to the field of particle granularity analysis and quality detection accuracy, and comprises the following steps: S1, calibrating an image acquisition module; s2, selecting proper standard sample particles; s3, calibrating the pixel size corresponding to the lens multiple; s4, testing accuracy self-correction verification of a dynamic image method particle size and shape analysis system is carried out, pixel accuracy calibration is optimized, and it is guaranteed that a standard particle testing result conforms to a standard particle special quantity value; and S5, establishing a dynamic image method particle size and particle shape analysis self-calibration standard curing method.

The embodiment of the invention discloses a photovoltaic power characteristic difference prediction method and system under different weather conditions and a medium. The method comprises the following steps: determining thermodynamic diagram data carrying dust type distribution information according to particle size analysis data; determining airflow turbulence characteristic parameters based on the three-dimensional velocity field data and the pressure distribution data; constructing a dust removal effect model according to the thermodynamic diagram data and the airflow turbulence characteristic parameters, and establishing a mapping relation between turbulence intensity and a dust removal effect; a power recovery speed prediction model is constructed according to the power output data of the photovoltaic panel under different dust removal effects, and a mapping relation between the dust removal effects and the power recovery speed is established; constructing a quantitative relation model under the severe convection weather condition based on the mapping relation; and according to the quantitative relation model and a preset photovoltaic power prediction model under a non-severe convection weather condition, constructing a photovoltaic power characteristic difference prediction model to perform photovoltaic power prediction under different weather conditions, thereby realizing accurate prediction of power recovery of the photovoltaic power station under severe convection weather.