2776results about "Particle size analysis" patented technology

The invention discloses a grinding machine internal part temperature anomaly detection method based on vibration signal analysis, which comprises the following steps that grinding data are collected through sensor deployment, and the sensors comprise a temperature sensor, a vibration sensor, an infrared thermal imaging sensor, a magnetic resistance current sensor and an inductance type particle sensor; carrying out preprocessing and feature extraction on the collected data; model construction and training are carried out based on data of preprocessing and feature extraction; according to the method, the abnormal condition of the temperature of the part is predicted by detecting the vibration signal of the internal part, the content of metal particles in lubricating oil is detected through the oil analysis sensor, and the abrasion degree of the bearing is judged in combination with the vibration signal. And motor current harmonic characteristics are monitored, and overload or rotor imbalance problems are identified.

The invention relates to the technical field of intelligent detection of building materials, in particular to a real-time detection method for grain composition characteristics of muck. The method comprises the following steps: S1, acquiring original point cloud data; s2, particle point cloud clustering; s3, determining the particle size of the sieved particles; s4, particle morphological feature extraction; s5, correcting the mass of the particles; and S6, grading feature output. The method has the characteristics of high precision, high efficiency, low cost, wide applicability and the like in particle grading characteristic detection, is particularly suitable for grading characteristic detection of residual mud particles, can also meet the real-time detection requirements of related particulate matters in other fields, such as mineral particle screening, building gravel detection, agricultural granular fertilizer grading and the like, and has a wide application prospect. Rapid and accurate detection of grain composition characteristics in different industries can be realized, and the requirements of various industrial production and engineering application are met.

The invention discloses a solar photovoltaic panel cleaning method and device based on a multi-mode cleaning technology, which can plan a traversal path according to parameters of a photovoltaic panel, primarily remove dust by using a wind blowing and ultrasonic vibration form, plan an energy-saving cleaning path for still existing cleaning points, and improve the cleaning efficiency of the photovoltaic panel. And secondary cleaning is conducted along the cleaning path, dust is adsorbed and cleaned through an electric field generated by the electrode plate, meanwhile, the output parameter set is trained and optimized through a trained deep learning model through input parameters extracted in real time, optimal cleaning parameters are obtained, and intelligent cleaning is achieved.

The invention provides a method for measuring the content of carbonate minerals, and belongs to the technical field of process mineralogy. The method for measuring the content of the carbonate minerals comprises the steps of ore grinding, reselection, automatic mineral analysis sample preparation, acid treatment, analysis comparison sample preparation, automatic mineralogy analysis testing, data correction and the like. Compared with the prior art, the analysis comparison sample is prepared in a targeted manner by introducing the analysis comparison sample for correction and combining automatic mineralogy analysis data, so that the analysis comparison sample is closer to an actual sample and is more representative, the test data is more accurate, and reliable data support is provided for efficient utilization of such resources.

Provided in the present invention are an imaging device and method for turbid oil abrasive particles based on polarized image enhancement, which belong to the technical field of image processing. The imaging device of the present invention includes a CMOS fixing device, a Stokes polarized CMOS sensor, an optical lens sleeve and an optical magnifying glass, where the Stokes polarized CMOS sensor includes a CMOS sensor and a Stokes analyzer. By using a polarization characteristic difference between scattered light of lubricating oil media and reflected light of abrasive particles, Stokes vector information is measured in real time under turbid lubricating oil scenes, the scattered light of the media is filtered out, image quality of the abrasive particles is improved, coverage duration for monitoring abrasive particle imaging is effectively prolonged.

The invention discloses an aerosol monitoring method and system based on clustering processing. The method comprises the steps of data acquisition, preprocessing, aerosol clustering and aerosol monitoring. The invention belongs to the field of data processing, and particularly relates to an aerosol monitoring method and system based on clustering processing, according to the scheme, a monitoring sub-model is customized for each monitoring station, specific pollution characteristics of the monitoring station are reflected, global regularization is carried out, and local monitoring is limited to deviate from global monitoring; the weight is dynamically adjusted based on the regional importance, the equipment quality and the acquisition time difference to ensure that the monitoring result reflects the latest pollution condition, so that the accuracy and reliability of the monitoring result are improved; the long-term pollution characteristics are reflected by introducing historical trend weights, result distortion caused by local deviation is avoided through global reference positions and correction, the long-term pollution trend can be reflected, short-term changes can be adapted, and then the aerosol monitoring accuracy is improved.

The invention relates to the technical field of boiler pulverized coal on-line detection, and discloses an automatic pulverized coal on-line detection device which comprises a pulverized coal sampling pipe suitable for being communicated with a pulverized coal pipe at an outlet of a coal mill; the screening devices are sequentially arranged in series, the first screening device is communicated with the output end of the pulverized coal sampling pipe, and the last screening device is communicated with an air extracting pump; the number of the weighing balances is multiple, the weighing balances and the screeners are arranged in a one-to-one correspondence mode, and the weighing balances and the screeners which are correspondingly arranged communicate with each other. Through automatic weighing and data recording, personal errors can be reduced, and the automation level of detection and the data reliability are improved. Through the arrangement that the pulverized coal sampling pipe is matched with the multi-stage screening device and the multi-stage weighing balance, the fineness of pulverized coal in the pulverized coal pipe at the outlet of the coal mill can be analyzed in real time, so that an operator is guided to timely and quickly adjust the coal mill in real time by utilizing the fineness analysis, and a boiler is enabled to operate in an optimal state; meanwhile, the cost of pulverized coal is controlled.

A diagnostic device and method for detection of a respiratory system infection of a subject, comprising a particle detecting unit configured for obtaining data related to particles being exhaled from the subject's airways, a processing unit for determining the respiratory system infection based on the data from the particle detecting unit and subject related properties.

The invention relates to the technical field of copper rod detection, in particular to a copper rod grain size detection method and system based on double-frequency eddy current analysis, and the method comprises the steps: synchronously obtaining a high-frequency eddy current response signal and a low-frequency eddy current response signal of the surface of a moving copper rod according to an orthogonally arranged double-frequency eddy current probe, and collecting the moving speed of the copper rod in real time; performing phase demodulation on the high-frequency eddy current response signal and the low-frequency eddy current response signal to respectively obtain a first phase angle and a second phase angle; calculating an instantaneous difference value between the first phase angle and the second phase angle, and generating an original phase difference characteristic quantity; performing dynamic compensation on the original phase difference characteristic quantity based on the movement speed of the copper rod to generate a speed compensation phase difference characteristic quantity; and inputting the speed compensation phase difference characteristic quantity into a pre-calibrated grain size mapping relation model to obtain a real-time grain size grade value. According to the invention, eddy current response interference caused by speed change in the continuous movement process of the copper rod is effectively eliminated, and high-precision detection of the grain size grade is realized.

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 provides a grain impurity rate and breakage rate monitoring system and method for a combine harvester. The grain impurity rate and breakage rate monitoring system comprises a grain sampling device, an image acquisition device and a control device, the grain sampling device is installed on the side wall of the vertical grain conveying barrel, a grain inlet of the grain sampling device is connected with a grain outlet hole in the side wall of the vertical grain conveying barrel through a hose, and a grain outlet of the grain sampling device is connected with a feeding port of the image acquisition device through a connecting pipe; the image acquisition device is connected with the control device, an image acquisition module of the control device controls the image acquisition device to acquire a grain image, and online calculation of the impurity rate and the breakage rate of the grain is realized on the grain image through a YOLOv8-Seg instance segmentation model of the image processing module in combination with an impurity rate and breakage rate mathematical model; finally, a detection result is displayed on a display screen in real time, visual numerical values can be provided for an operator of the combine harvester, and the operator is helped to adjust working parameters of the harvester. The method can be used for harvesting rice, wheat, oilseed rape and soybeans, and has wide applicability.

The invention provides an environment detection method and system. The method comprises the following steps: detecting spectral information of each soil sample through an intelligent spectral sensor; extracting a reference spectral value from the spectral information of each soil sample, and determining an absorption spectrum of the pollutants according to the reference spectral value and the spectral information; performing principal component analysis on the absorption spectrum to obtain a spectral characteristic value of each soil sample in principal component, and determining a spectral fluctuation quantity based on each spectral characteristic value; acquiring granularity information of each soil sample by using an intelligent sound wave granularity sensor, and determining interaction characteristics of each soil sample according to the granularity information of each soil sample; and determining a confidence characteristic spectral line according to all the spectrum fluctuation quantities and all the interaction characteristics, and further detecting the content of the pollutants in the target environment through the confidence characteristic spectral line. By adopting the scheme provided by the invention, the influence of heterogeneity of the soil sample on the characteristic spectral line can be avoided, so that the content detection precision of pollutants is improved.

The invention relates to a GIS particle defect evaluation method and equipment fusing vibration and partial discharge, and the method comprises the steps: obtaining an ultrasonic signal and an ultrahigh frequency signal caused by the partial discharge of a GIS, generating a phase distribution diagram of the partial discharge, comparing the phase distribution diagram with a reference map, and judging whether a particle defect exists or not; for particle defects, the particle size is calculated based on the average discharge capacity and the maximum discharge capacity of the ultrahigh-frequency signals; and acquiring a vibration signal, combining the calculated particle size, outputting the predicted particle horizontal diffusion area and the maximum jumping height, and calculating a danger degree index of the particle defect so as to evaluate the danger degree of the GIS particle defect. Compared with the prior art, the method has the advantages that the sensitivity, the accuracy and the real-time performance of detection are improved, and more comprehensive evaluation is provided for the health state of the GIS equipment.

The invention discloses a method for measuring the particle size of metal powder by using a scanning electron microscope, which comprises the following steps: step 1, sample treatment: adhering a small conductive adhesive tape on a sample table, sprinkling metal powder on the adhered conductive adhesive tape, and purging to obtain the conductive adhesive tape adhered with the metal powder; step 2, parameter setting: setting acceleration voltage, working distance, diaphragm, image contrast, brightness, magnification times and scanning speed of a scanning electron microscope to observe the conductive adhesive tape adhered with the metal powder obtained in the step 1 to obtain an electronic image of metal powder particles; and processing and calculating the electronic image of the metal powder particles by using software to obtain the average particle size of the metal powder particles. According to the method disclosed by the invention, a solvent is not needed to disperse the sample, pollution of the solvent to the sample is effectively avoided, and the result is more accurate than that of directly measuring the particle size by using length software.

The invention relates to a powder coating particle size automatic analysis method, which comprises the following steps: obtaining a powder coating particle image shot by an electron microscope, carrying out feature extraction on the particle image to obtain a plurality of feature maps, dividing each feature map into image blocks with the same size, obtaining areas of the image blocks on the particle image, obtaining a foreground score of the image block by using the average gray value and the contour line length of the region; selecting a plurality of target image blocks from each feature map according to the foreground score and particle size distribution information in the particle image, calculating the attention of the target image blocks at each layer of the encoder, and then calculating the attention of the target image blocks and the filtered image blocks based on the average gray value; and obtaining an output corresponding to the target image block in the encoder, taking the output as an input of a decoder, obtaining a particle frame in the particle image through the decoder, and obtaining particle size information of the powder coating according to the particle frame.

The invention discloses a slurry detection device and method and a slurry coating system, and relates to the technical field of batteries. The conductive liquid and the target particulate matter filtered from the battery slurry sample are accommodated in the insulating groove, and the liquid and the target particulate matter in the insulating groove can flow into the hole pipe through the hole under the condition that the internal pressure of the hole pipe is greater than the external pressure. When target particles enter the hole pipe through the hole, a voltage pulse signal is generated. At the moment, the voltage sampling circuit connected in parallel with the direct-current power supply can detect the voltage pulse signal, and then the particle condition in the battery slurry can be determined according to the voltage pulse signal. Therefore, according to the slurry detection device provided by the embodiment of the invention, the particle condition of the battery slurry can be directly determined through the collected voltage pulse signal, manual observation and analysis through a microscope are not needed, the production efficiency is improved, and the potential safety hazard is reduced.

The invention discloses a method for identifying the stability of granular sludge based on microbial activity change characteristics. The method comprises the following steps: taking a certain amount of sludge at the aeration tail end of an AGS device as a sample; the method comprises the following steps: putting a sample into a transparent measuring cylinder, judging the settling performance of granular sludge, quantitatively detecting the cell activity of microorganisms in the sludge by using a flow cytometer, and meanwhile, carrying out online monitoring on the sludge sample of an aerobic granular sludge system by using a respiration graph measuring device (LB-WBM-450PI type smart workstation). Through multi-dimensional analysis of sedimentation characteristics, microbial metabolic activity and flow cytometry activity of the aerobic granular sludge, characteristic information such as particle morphological structure integrity, dynamic change between the microbial metabolic activity and the flow cytometry activity and the like can be provided, and data support is provided for stability regulation and control research of the aerobic granular sludge.

The invention relates to the related technical field of dust detection, and provides a mining induced charge and light scattering fusion dust detection device and method.The dust detection device comprises a workbench, a sampling assembly and a detection assembly, and the sampling assembly comprises a sampling air pump, a conical airflow homogenizer and a closed sampling cavity; the detection assembly comprises an annular sliding rail, a light scattering detection module and an electrostatic induction detection module; the dust detection method comprises the following steps: S1, device initialization and zero calibration; s2, sampling preparation of dust-containing airflow; s3, dual-module synchronous signal acquisition; s4, data processing and temperature and humidity compensation; s5, carrying out anti-interference protection assembly; and S6, data fusion and result output. S7, device cleaning and standby; through cooperative work of the double detection modules, dust detection signals in different concentration intervals are accurately captured, wide-range coverage from low concentration to high concentration is achieved, and synchronous monitoring of dust concentration and particle size characteristics is achieved.

The invention discloses a bed load sediment transport rate measurement method based on multi-layer sediment acoustic signal attenuation correction of a Doppler velocity profiler, which comprises the following steps: sampling sediment on the surface of a riverbed in an overtopping area of a to-be-measured river reach, and measuring sediment gradation to obtain the median particle size of the bed sediment; obtaining flow measurement data, and extracting ship speed data from the flow measurement data; calculating a riverbed movement speed according to the ship speed data; filtering the riverbed movement speed data, and calculating a characteristic value of the filtered riverbed movement speed data; respectively calculating the vertical projection area ratio of bed load according to the filtered riverbed movement speed data characteristic values; calculating a dimensionless sediment particle size according to the median particle size of the bed sand; calculating the thickness of a bed load layer according to the dimensionless sediment particle size; calculating the volume concentration of the bed load according to the vertical projection area ratio of the bed load and the thickness of the bed load layer; calculating a multi-layer sediment sound signal attenuation correction coefficient according to the bed load volume concentration; and calculating the bed load sediment transport rate according to the multi-layer sediment sound signal attenuation correction coefficient. The bed load sediment transport rate can be accurately and effectively measured.

Disclosed is a system for optimizing a particle size distribution of a lost circulation material. The system comprises a data acquisition module, a communication module, an experimental module, a particle size distribution optimization module, and a plugging and filling module. The data acquisition module is configured to obtain a target feature particle size. The experimental module is configured to obtain the target feature particle size, and set a plurality of experimental schemes for fracture plugging; conduct fracture plugging experiments to obtain experimental results; evaluate a plurality of fracture plugging effects of each of the plurality of experimental schemes. The particle size distribution optimization module is configured to obtain the plurality of fracture plugging effects, determine a particle size distribution rule, and obtain optimized particle size distribution data by optimizing the particle size distribution of the lost circulation material. The plugging and filling module is configured to perform a plugging operation.

The invention relates to the technical field of sediment monitoring equipment, and discloses an online pipeline particle monitoring system based on ultrasonic detection, which solves the problem of low monitoring accuracy, and comprises a to-be-detected pipeline, the outside of the to-be-detected pipeline is slidably connected with a front fixing belt and a rear fixing belt, and the top of the front fixing belt is provided with a monitor lower shell. A plurality of ultrasonic detectors and a processing module are arranged at the top of the monitor lower shell, an alarm is arranged at the top of the monitor lower shell, a supporting column is arranged in the to-be-detected pipeline, a cleaning knife is arranged at the left end of the supporting column, a cleaning disc is arranged at the rear end of the cleaning knife, and moving wheels are arranged outside the supporting column; through a non-contact monitoring method, the ultrasonic signals generated when silt impacts the pipe wall are obtained, the granularity and the wave crest and wave trough density are judged according to the amplitude of the amplified frequency domain electric signals to judge the number, the characteristics of the silt in the pipeline are well reflected, and therefore the monitoring efficiency is improved.

The invention discloses a wind power generation equipment gearbox oil state detection method and system, and the method comprises the steps: obtaining an oil sample, carrying out the quantitative analysis of solid, liquid and gas pollutants through an oil pollution degree analysis model, and processing the parameters such as kinematic viscosity through an oil physicochemical property analysis model; and after the tensors of the two results are fused, feature decoupling and deep feature mining are performed, and finally, the oil state is judged by a state evaluation decision model. The system is correspondingly provided with six units such as a sample acquisition unit and a pollution analysis unit to realize the functions. According to the scheme, the defects that traditional detection is single and correlation analysis is lacked are overcome, a certain index is not independently detected any more, pollution and physicochemical property information is comprehensively integrated, the relation between the pollution and the physicochemical property information is deeply analyzed through tensor fusion, feature decoupling and other technical means, accurate evaluation of the oil state of the gearbox is achieved, and the detection accuracy is improved. And misjudgment caused by one-sided detection or no consideration of mutual relations is effectively avoided.

The invention provides a system and method for detecting free carbon particles in transformer oil based on a microelectrode array, and the system comprises a sampling module which comprises an oil inlet pipeline and a filtering device, an oil sample is conveyed to a microelectrode array sensor module from a transformer oil tank through the oil inlet pipeline, and the filtering device is located in the oil inlet pipeline; a filter membrane is arranged in the filter device to remove impurities in the oil sample; the microelectrode array sensor module comprises a microelectrode array sensor, the microelectrode array sensor is nanoelectrodes arranged on a silicon substrate, the surface of the microelectrode array sensor is coated with graphene oxide to adsorb free carbon particles in an oil sample, and when the free carbon particles are adsorbed to the surface of the microelectrode array sensor, an adsorption signal is generated; and the signal processing unit is used for extracting the characteristic frequency and intensity of the vibration of the carbon particles in the adsorption signal, and classifying the carbon particles according to the characteristic frequency and intensity of the carbon particles. The device is compact in structure, the maintenance cost is reduced, and the operation process is simplified.

Methods and systems for water quality assessment are disclosed. The method includes obtaining a first input data indicative of properties of a first liquid sample, the first input data including turbidity data and total suspended solids data for the first liquid sample, where the first liquid sample is acquired from a liquid source. The method further includes determining, using a computer processor and a machine learning model, a first predicted particle-size distribution of the first liquid sample based on the first input data, where particle-size distribution is controlled, at least in part, by a set of dosage parameters configurable by a water quality system. The method further includes determining, with an optimizer applied to the machine learning model, an optimal set of dosage parameters based on the first predicted particle-size distribution and adjusting the set of dosage parameters of the water quality system to the optimal set of dosage parameters.

The invention relates to a detection method and application of a bainite steel structure and / or grain boundary for nuclear power equipment, and relates to the technical field of new material detection. According to the detection method, the problem that the structure and the grain boundary of bainite steel for nuclear power equipment are difficult to display can be solved, a major breakthrough of a grain size detection technology is achieved, the clear and complete grain boundary can be accurately presented, and scientific evaluation of the grain size through a comparison method, a cut point method, an area method and the like according to standard requirements is further supported. When the detection method is used for evaluating the grain size, the results are highly consistent, the repeatability is good, and the problems of subjective experience dependence and measurement errors caused by blurred grain boundary display in a traditional nitric acid and alcohol corrosion method are effectively avoided.

The invention belongs to the technical field of sediment particle size monitoring, and particularly relates to a sediment particle size monitoring device for river flow monitoring, which comprises at least three conical barrels sequentially sleeved from left to right, and the outer barrel wall of the conical barrels sequentially sleeved from left to right is in non-contact design with the other outer barrel wall. Meshes formed in the cylinder wall of the conical cylinder located on the left side are located in the conical cylinder located on the right side, the diameters of the meshes formed in the cylinder walls of the three conical cylinders from left to right are sequentially decreased, and a particle size monitoring assembly is detachably installed at the cylinder opening of the conical cylinder located on the leftmost side through a supporting mechanism; the at least three conical barrels are installed in a river channel to be monitored in a settling mode through the supporting settling assemblies. The monitoring device provided by the invention not only can be used for monitoring the particle size of the sediment particles mixed in the river, but also can be used for collecting and sampling the monitored sediment particles in a grading manner, so that the application range of the monitoring device provided by the invention can be widened.

The present invention discloses an emulsified asphalt storage stability analysis method and system, the method comprising: judging whether a first diameter difference between a first layer average particle diameter and a second layer average particle diameter is greater than a preset threshold value; if greater than the preset threshold value, selecting a target first layer average particle diameter from other first layer average particle diameters according to a preset selection strategy; subtracting a target second layer average particle diameter corresponding to the target first layer average particle diameter from a second layer average particle diameter to obtain a second diameter difference, and judging whether the second diameter difference is greater than a preset threshold value; assigning weights to the first stability result and the second stability result according to a first ratio of the first diameter difference to the target difference and a second ratio of the second diameter difference to the target difference. The first stability result can be corrected, thereby improving the authenticity of the emulsified asphalt stability determination in a storage tank as much as possible.

The invention discloses a soil nitrogen leaching capacity monitoring method based on a frequency domain reflectometry, and relates to the technical field of soil water environment monitoring, in particular to a nitrogen leaching online monitoring method based on the frequency domain reflectometry (FDR), the Darcy law and a Van Genuchten (VG) model. And a monitoring method with high precision and sensitivity, multi-parameter synchronous detection and low cost is provided for the soil nitrogen leaching capacity. Comprising the following steps: 1, collecting and pretreating a soil sample; 2, placing the treated soil sample in a soil experiment cylinder; 3, inserting the multi-parameter sensors into the soil experiment cylinder in a layered manner; 4, 1000 ml of water is injected, and data acquisition is carried out; and 5, realizing soil nitrogen leaching capacity monitoring in combination with a Darcy law and a VG model.

The invention provides a sensor fusion-based pig feed crushing particle size monitoring method, which comprises the following steps of: synchronously acquiring vibration, acoustic emission and optical signals, carrying out band-pass filtering, normalization, feature extraction and wavelet packet decomposition, and dynamically adjusting the confidence coefficient of each channel in combination with working condition perception and a sensor performance knowledge base so as to monitor the crushing particle size of the pig feed. Weighted fusion and conflict evidence modulation of multi-source signals are achieved, the improved Dempster-Shafer evidence theory is introduced to improve the abnormal granularity recognition accuracy, key parameters of crushing equipment are controlled in a linkage mode through a closed-loop feedback mechanism, high-robustness detection and self-adaptive adjustment of the granularity state are achieved, and the method has the advantages of being high in robustness and high in robustness. And the stability and the automation level of the feed crushing process are improved.

Analytical methods and systems for assessing analyte distribution uniformity in cosmetic compositions are provided. An analysis system (1) for evaluating analyte distribution uniformity of a cosmetic composition comprises: a binarization and calibration module (41) for binarizing and calibrating a chemical image of the cosmetic composition to obtain a binarized and calibrated image; the image segmentation module (42) is used for splitting the binarized and calibrated image into small grids; and an analyte distribution uniformity evaluation module (43) for calculating the number of pixels corresponding to the analyte in the small grid to obtain an analyte distribution uniformity.