6523 results about "Particulates" patented technology

The invention discloses a clean workshop production environment quality control method and system, and relates to the technical field of environment control, and the method comprises the steps: constructing a multi-layer sensing network, deploying temperature and humidity, particle concentration, pressure difference and VOC gas sensors, and carrying out the preprocessing data of each node through edge calculation; fusing the data based on a dynamic weight distribution algorithm, adjusting the weight according to the confidence score, and generating an environment quality comprehensive index; an LSTM pollution diffusion prediction model is established, a diffusion path is calculated in combination with airflow field simulation when pollution suddenly occurs, and an emergency response partition strategy is generated; fresh air system control parameters are optimized through reinforcement learning, a dynamic ventilation frequency adjusting model is established based on a real-time environment quality index and historical energy consumption data, and energy consumption is minimized through a Q-learning algorithm on the premise that cleanliness is guaranteed; a double-threshold early warning mechanism is set, local supercharging purification is started when a comprehensive index exceeds a first-level threshold, a second-level threshold is linked with adjacent areas to form a dynamic isolation barrier, and an intervention scheme effect is simulated through a digital twin system.

A batch feeding-based multi-stage screening device for granular materials, comprising a housing (1). A quantification assembly (2) is installed at the top of the housing (1), a dust removal assembly (3) is installed outside the housing (1), and an anti-blocking assembly (6) is installed inside the housing (1); the dust removal assembly (3) comprises a mounting plate (305) and a fixed column (304); the mounting plate (305) and the fixed column (304) are both fixedly connected to the outside of the housing (1), a rack plate (306) is slidably connected to the outer surface of the mounting plate (305), a movable rod (311) is fixedly connected to the bottom end of the rack plate (306), a rubber piston (312) is fixedly connected to the bottom end of the movable rod (311), and a filter box (301) is fixedly connected to the outside of the housing (1). A large amount of dust on the surface of rice grains can be adsorbed, filtered and removed by means of the dust removal assembly, thereby improving the quality of rice.

The invention provides a particulate matter and ozone source monitoring method and system based on a distributed sensor, and relates to the technical field of pollution treatment. According to the invention, sensor nodes with geographic perception capability are deployed in a monitoring area in a high-density manner, pollutant concentration and meteorological parameters are collected in real time, and data are uploaded to a cloud platform for preprocessing and dynamic calibration; a machine learning model is constructed based on the combined features of the pollutants and the meteorological factors, a driving relation is mined, and pollutant influence factors are extracted; further performing joint modeling on the influence factors and regional emission source data, identifying the coupling strength between pollutants and emission sources by adopting a classification or clustering method, and judging the categories of main sources; backward trajectory simulation, source fingerprint analysis and multi-source regression decomposition are combined to realize pollution path inversion and source contribution rate quantification; and finally, constructing a geographic information visualization platform, displaying a pollution thermodynamic diagram, a contribution change diagram and an evolution path diagram, and providing support for multi-source pollution traceability and scientific management and control.

The invention relates to the technical field of water pollution detection, in particular to a water quality pollution multi-dimensional analysis system which comprises the following steps: synchronously measuring an ultraviolet-visible absorption spectrum of a water sample to be detected and scattered light intensity in an orthogonal direction, and deducting spectrum baseline interference caused by suspended particulate matters in the water sample through a correction algorithm; the interferents in the water sample are selectively converted and degraded by applying a programmed potential to the inflowing water sample to be detected; the reverse pulse is periodically applied, so that the online regeneration function of the electrode is realized; analyzing the spectral data by adopting a multivariate correction algorithm, and calculating the concentration of the target pollutant; the calculation residual error of the multivariate correction algorithm is analyzed, new interference and system performance drift of current measurement are diagnosed, and a corresponding system state code is generated; and responding to the system state code, automatically starting and carrying out state checking and multi-point calibration on the instrument, and using a calibration result to update the analysis model. Through multi-dimensional perception and closed-loop operation, accuracy and reliability of water quality monitoring are guaranteed.

A material removal system includes a collection conduit having a distal end that is positionable adjacent particulate material. A primary particle separator system connected to the collection conduit separates quantities of particulate material entrained in an air stream. A secondary particle separator system connected to an outlet of the primary particle separator system separates additional quantities of particulate material entrained in an air stream exiting the primary particle separator system. An air pump connected to an outlet of the secondary particle separator system creates an airflow through the collection conduit and the primary and secondary particle separator systems. A conveyor system operatively associated with material discharge ports of the primary and secondary particle separator systems collects separated particulate material from the material discharge ports of the primary and secondary particle separator systems and transports the separated particulate material to a material discharge end of the conveyor system.

An IAQ sensor module includes: a sensor configured to measure an amount of an item in air, the item being one of particulate matter, volatile organic compounds, and carbon dioxide; a minimum module configured to selectively store the amount of the item as a minimum value of the amount when a mitigation device has been on for at least a predetermined period, the mitigation device being configured to decrease the amount of the item in the air when on; a storing module configured to selectively store the minimum value as an initial minimum value; an offset module configured to determine a drift offset for the sensor based on a difference between the minimum value and the initial minimum value; and an adjustment module configured to determine an adjusted amount of the item in the air at the IAQ sensor module based on the amount and the drift offset.

The invention relates to the technical field of particulate matter sampling analysis, and discloses a full-automatic multi-point sampling system and method for particulate matters in a large flue. The system comprises an analysis module for acquiring airflow data through an airflow parameter sensor; the arrangement module is used for optimizing sampling point positions according to the airflow data; the monitoring module monitors particulate matter distribution in real time; the acquisition module is used for acquiring samples by adopting a gradient constant-speed strategy; the generation module is used for analyzing the sample to generate a component characteristic spectrum; and the fusion module comprehensively analyzes and generates a detection report. According to the application, full-automatic multi-point sampling and comprehensive analysis of the particulate matters in the large flue are realized, the defects of strong dependence on manual operation, limited sampling point positions, incapability of adapting to a complex flue environment and the like in a traditional sampling method are overcome, and the accuracy, representativeness and working efficiency of particulate matter sampling are improved.

According to the dynamic traffic environment monitoring method and device provided by the embodiment of the invention, the mobile sampling of pollutants such as particulate matters, nitrogen oxides and carbon monoxide is realized by constructing a power-assisted bicycle environment monitoring and collecting network. And the cloud computing platform performs abnormal value identification based on time sequence clustering, constructs a pollutant concentration distribution model through a multivariate convolutional neural network, and generates diffusion trend prediction in combination with a pollutant migration model. And intelligent scheduling of monitoring resources is realized by adopting a deep reinforcement learning algorithm, and an optimized inspection scheme is generated according to the pollution risk level, the vehicle position and the electric quantity. According to the method, the defects of the traditional technology in the aspects of monitoring coverage, data analysis, resource scheduling and the like are effectively overcome, and the accuracy and the practical value of traffic environment monitoring are remarkably improved.

The invention relates to the technical field of big data monitoring, in particular to a highway environmental protection construction monitoring method and system based on big data, and the method comprises the following steps: calculating the spatial distance between sensors based on the geographic position information of a data collection point and the raised dust concentration distribution and particulate matter monitoring value of a road construction environment, and calculating the spatial distance between sensors; and connecting sensor nodes with a direct adjacency relation through difference calculation and normalization processing. According to the invention, through probability density calculation and time sequence analysis, abnormal edge screening, abnormal change detection precision improvement, misjudgment reduction, abnormal edge connection node position and space density calculation, high-density area and cluster center determination, accurate positioning of pollution points is realized, and the method is suitable for the real-time monitoring of the pollution points in combination with monitoring data change trend and diffusion path tracing. The method comprises the following steps: reconstructing a pollution diffusion chain, determining a pollution propagation range, optimizing pollution treatment, accurately identifying a pollution source through weight association degree and gradient analysis between path nodes, reducing monitoring blind areas, and providing comprehensive support for construction monitoring.

A pump side part for use with a centrifugal slurry pump for pumping a fluid mixture containing particulate matter, the pump side part comprising a main body having a main axis, the main body including a side wall section which extends laterally with respect to the main axis and has opposite facing first and second sides, a plurality of formations on a surface of the second side including an inner formation and an outer formation in spaced relation to the inner formation, the formations being configured so that in use the formations generate a flow of the fluid mixture across the surface which detaches from the surface the particulate matter adjacent thereto.

The invention relates to the technical field of data processing, and discloses an incremental clustering method and system for an atmospheric aerosol particulate matter mass spectrum data set, a terminal and a storage medium, and the method comprises the steps: obtaining the atmospheric aerosol particulate matter mass spectrum data set, and carrying out the clustering initialization processing, and obtaining a plurality of clustering initialization parameters; determining a target cluster selection strategy, and performing first similarity calculation and cluster allocation processing on the plurality of cluster initialization parameters to obtain a plurality of cluster center matrixes; performing merging processing and de-noising processing on the plurality of cluster center matrixes to obtain an initial clustering result, and performing second similarity calculation to obtain an iterative similarity; and performing clustering convergence judgment and iterative loop clustering processing on the initial clustering result, and outputting a clustering result of the atmospheric aerosol particulate mass spectrum data set. According to the method, the inter-cluster mixing condition in the clustering analysis process of the atmospheric aerosol particulate matter mass spectrum data set can be remarkably reduced, and the accuracy of clustering result output is ensured.

The invention relates to the technical field of optical particulate matter sensing, in particular to a particulate matter particle size recognition and concentration detection method. The method comprises the following steps: laser emitted by a laser forms a laser beam which is focused and then diverged through a lens; with a laser focus as a reference, at least two photosensitive devices are distributed in the light beam propagation direction and comprise a perifocus device and a far focus device, and receiving surfaces of the near focus device and the far focus device face laser beams to collect scattered light; scattered light signals of each device are collected, and are input into a processing unit after independent current / voltage conversion, signal amplification and analog-to-digital conversion; based on the characteristics that small-particle-size scattered light is preferentially captured by perifocus high irradiance and large-particle-size scattered light is preferentially captured by far focus large beam diameter, a mapping relation between particle sizes and channels is established; the number concentration and mass concentration coefficient of each channel is calibrated through standard particles, and synchronous detection of PM1.0, PM2.5 and PM10 is realized in combination with linear processing, so that the particle size recognition precision and the concentration measurement reliability are effectively improved.

The invention discloses a self-cleaning mechanism of a differential rotation type multi-stage air purification filter cartridge, and relates to the technical field of air purification equipment. The device comprises a purification shell, a first filter cartridge is arranged in the purification shell, the surface of the first filter cartridge is sleeved with a second filter cartridge, and the surface of the second filter cartridge is sleeved with a third filter cartridge; a driving assembly is arranged at the top of the purifying shell and comprises a driving motor arranged at the top of the purifying shell and a transmission rod installed at the output end of the driving motor. Through meshing transmission of a sun gear and a planetary gear in the driving assembly, differential rotation of the first filter cartridge and the second filter cartridge is achieved, attached particles are stripped in a layered mode through centrifugal force, the self-cleaning efficiency is remarkably improved, the differential design breaks through a static filtering mode of a traditional filter cartridge, particulate matter deposition inertia can be actively destroyed, and surface dust accumulation of a filter material is reduced; the problem of filtering efficiency attenuation caused by dust accumulation is avoided, the service life of the filter cartridge is prolonged, and the maintenance frequency is reduced.

The invention discloses a rotor punching and stacking welding defect identification system based on edge calculation, and relates to the technical field of rotor welding identification, and the rotor punching and stacking welding defect identification system comprises a data acquisition module which is used for carrying out real-time acquisition on smoke dust data generated in the welding process, and the smoke dust data comprises smoke concentration, suspended particulate matter concentration and smoke infrared thermal imaging temperature; the model matching module is used for comparing the smoke concentration, the suspended particulate matter concentration and the smoke infrared thermal imaging temperature with corresponding preset reference models respectively to obtain abnormal data with an abnormal trend; and the judgment module is used for performing time sequence analysis on the abnormal data, calculating a standard deviation and a mean deviation rate based on a sliding window, and generating a corresponding early warning growth value. According to the method, a dynamic alarm value generation and attenuation mechanism is constructed, so that false alarm caused by continuous influence of historical data is avoided, and the real-time response accuracy of the integrated value is improved. And through a pre-judgment mechanism, it is ensured that alarm value attenuation is executed only on the premise that data are stable or no early warning growth trend exists.

The invention provides a construction method and system of a rock-soil shear strength parameter prediction model, and relates to the technical field of model construction.The construction method comprises the steps that CT scanning data of a real rock-soil sample is obtained and preprocessed, and an irregular three-dimensional particle set for geometric modeling is obtained; performing particle surface roughness modeling analysis on the three-dimensional particle body set to obtain a surface roughness coefficient set of the three-dimensional particle body set; performing particle size cumulative distribution function segmentation processing and fractal dimension control on the surface roughness coefficient set to obtain a structure grading sample set; constructing a THMC multi-field coupling model based on the structure grading sample set to obtain a working condition particulate matter physical response parameter set; and performing a simulation experiment on the working condition particle physical response parameter set, and performing deep neural network modeling processing based on an experiment result to obtain a strength response model capable of predicting the cohesive force and the internal friction angle of the rock-soil body under any working condition input. According to the invention, the prediction efficiency and accuracy are significantly improved.

The invention discloses a dynamic blockage management system and method for an underground water recharge well. The system comprises a monitoring and acquisition module, a data processing and risk assessment module, a flow rate adjustment optimization and dynamic feedback module and a storage and remote management module. The method comprises the following steps: monitoring key parameters such as water flow rate, suspended particulate matter concentration, fluid density and temperature and the like in a well injection process in real time, and carrying out data preprocessing; deriving a comprehensive blockage risk index calculation formula based on the key parameters, and comparing with a set threshold to judge whether flow velocity adjustment is triggered or not; by analyzing the relationship among the blockage risk, the pressure loss and the injection amount in real time, an objective function is constructed to seek an optimal solution; the well injection flow velocity is dynamically adjusted based on the solved optimal flow velocity and is dynamically fed back; and carrying out data storage and remote management. The device can dynamically adjust the injection flow rate, remarkably improve the injection efficiency, reduce the maintenance cost, and effectively manage and reduce the physical blockage problem in the underground water recharge process.

The invention relates to a wafer cleaning solution and a cleaning method, the cleaning solution is used for an SC-2 cleaning process, and the cleaning solution comprises hydrochloric acid, hydrogen peroxide and deionized water; wherein the pH value of the cleaning solution is greater than 2. According to the invention, particulate matters can be effectively prevented from depositing on the surface of the wafer, so that the deposition quantity of the particulate matters on the surface of the wafer is reduced, and the cleaning effect on the wafer is improved.

A device for dosing particulate material uses multiple valve plates to collectively open or close a discharge port, so that an opening degree of the discharge port can be adjusted according to the degree to which the adjustment ends of each valve plate are gathered, thereby effectively adjusting the opening degree of the discharge port. When the amount of particulate material to be dosed is large, the opening degree of the discharge port can be increased accordingly to increase the discharge speed of the particulate material, shortening the discharge time and improving the efficiency of dosing. Furthermore, the opening degree of the discharge port can be adjusted to be adapted with particulate material of different volumes, such that larger particulate material can also smoothly pass through the discharge port to avoid blockage of the discharge port.

The invention belongs to the field of atmospheric environment particulate matter monitoring, and particularly relates to an atmospheric environment salt mist concentration real-time monitoring device and method. The monitoring device comprises a computer control module, a container and a buoy, a conductivity electrode, a temperature sensor, a displacement sensor, an air inlet pipe and an air outlet pipe are integrated on the top of the container, and the air outlet pipe is connected with a reciprocating cylinder with a piston and a limit switch. The monitoring method comprises the following steps: calibrating the initial volume V < initial > of liquid and the volume V < initial > of a reciprocating cylinder; circularly collecting the conductivity k0 and k1, the temperature T0 and T1 and the displacement D and Dtotal of the buoy before and after ventilation; correcting the salt mass increment delta M through the dynamic volume, and finally outputting the salt mist concentration C; according to the invention, the defects of inaccurate ventilation volume metering, solution density change and interference of moisture in high-humidity air on concentration monitoring in the prior art are overcome, full-automatic continuous monitoring of the salt mist concentration is realized, the measurement error is effectively reduced, the measurement precision and the monitoring capability are remarkably improved, and the method has relatively good environmental adaptability.

The invention discloses an urban particulate matter migration path identification method based on data fusion of a dynamic diffusion model and multi-source sensing. According to the method, firstly, multi-source pollution related data of a fixed monitoring station, a mobile monitoring device, a meteorological observation node and a traffic sensing system are collected, and standardized input is constructed after time synchronization, coordinate mapping and exception handling. And then establishing a hybrid dynamic diffusion model fusing a two-dimensional Gaussian plume model and a Lagrange particle tracking mechanism, and realizing assimilation of monitoring data and model output in combination with an improved particle filtering algorithm to obtain a correction concentration field. Based on concentration gradient analysis and particle trajectory superposition, a pollution migration path is extracted, then indexes such as a migration intensity index (MII), a path stability factor (PSF) and path average correlation are calculated, and recognition and sorting of a migration direction, a pollution source position and path stability are achieved. Meanwhile, an alpha dynamic weight factor is introduced, adaptive weighting is realized between the Gaussian model and the LPDM model, and the path strength and consistency are considered. Experimental results show that the method is superior to a traditional method in average absolute deviation (MAD) and hot spot overlap ratio (IoU) indexes, diffusion and migration rules of particulate matters under complex urban conditions can be more accurately revealed, and the method has important environmental governance and emergency management application value.

The invention discloses a modularized ultrapure water preparation and on-line monitoring system, which comprises a pretreatment module, a purification module, a monitoring module and a control module, and is characterized in that a dynamic monitoring end is arranged, and when ultrapure water preparation is monitored in real time, a multi-parameter fusion detection mechanism and self-adaptive threshold analysis are integrated; meanwhile, the abnormal state of the water quality is dynamically judged based on the conductivity, TOC and particulate matter data collected in real time, the sudden change risk of the water quality output by the purification module can be recognized in real time, error accumulation caused by traditional single-point monitoring is avoided, and therefore the purity detection reliability of the ultrapure water is improved; and the reverse osmosis unit and the electrode deionization unit of the purification module can immediately respond to the effluent parameter change of the pretreatment module, so that the hidden dangers of membrane blockage and recovery rate reduction caused by water quality fluctuation are reduced, and the energy consumption redundancy is reduced while the water quality stability is ensured.

The invention discloses a composite efficient heat dissipation type modular data center, and belongs to the technical field of data centers, the composite efficient heat dissipation type modular data center comprises a data module and a data cabinet body provided with a liquid cooling center and an air cooling center, an integrated data seat is arranged in the data cabinet body, and a liquid cooling pipe distribution chamber is arranged between the back of the integrated data seat and the data cabinet body; the integrated data base is provided with a plurality of module slots for the data modules to be inserted, and the side walls of the two sides of the opening of the data cabinet body are provided with wind blocking partition plates. Through the combined design of liquid cooling and air cooling, when a data module in the data center is burnt down due to a fault, particulate matters generated by the data module can be rapidly sucked away by strong suction force generated by the air suction opening in the air blocking partition plate and are discharged through the air backflow cavity; particulate matters generated by burning are prevented from being blown away by air cooling airflow and polluting adjacent health data modules, and the risk of secondary pollution and the cleaning difficulty in the maintenance process are greatly reduced.

The invention provides a thermal stratification reservoir particulate matter settlement motion test simulation device and method, and the device comprises a design stage, a test preparation stage, a preparation stage, a particle size measurement stage, a settlement test stage, a data processing and analysis stage and a test result stage. According to the method, the resistance coefficient CD and the Reynolds number parameter are calculated, the response relation between the resistance coefficient CD and the Reynolds number parameter and the particle morphology index is analyzed, the particle settling velocity is corrected, the influences of the fluid viscosity, the particle shape, the temperature gradient, the measurement error and other factors are considered, and the test result is more accurate and reliable.

The invention relates to an operating room air quality dynamic monitoring analysis method, which is characterized by comprising the following specific steps of: creating a plurality of sampling areas for monitoring air quality around an operating bed in an operating area in advance, and continuously collecting and storing the quantity and the concentration of particulate matters in different particle size ranges in air in different sampling areas; by monitoring personnel access conditions, different operation types, different cleaning modes and different material distribution methods, data support is provided for improving control quality, the influence of different environmental changes on particulate matters in air is analyzed, and then control can be performed by adopting positive means according to analysis results. The air quality data of the operation core area and the peripheral area can be obtained through the multiple sampling areas, the data are stored to form a continuous air quality broken line graph, the air quality full view of the whole day is truly restored, and therefore the air quality in the operating room is improved.

The invention discloses an intelligent laser testing method, which relates to the field of laser testing, and comprises the following steps: judging whether a laser has a fault or not by monitoring the fluctuation amplitude of optical power at the initial stage of starting a to-be-tested laser to emit a light beam; after the laser is not judged to have a fault, the influence of environment heat radiation or aerosol particles on the light beam is positioned by collecting temperature gradient distribution data of a light beam propagation path and combining with air particulate matter concentration data; and obtaining a light beam drift direction, a drift speed and energy uniformity on a light beam propagation path based on the light spot image, determining an abnormal position according to changes of the light beam drift direction, the drift speed and the energy uniformity, and associating the abnormal position with the temperature gradient and the particulate matter concentration in real time. The method effectively distinguishes the fault of the laser from the environmental interference, accurately locates the abnormal position on the beam propagation path, and determines the main environmental interference factors causing the dynamic quality degradation of the beam, thereby providing an accurate basis for the performance evaluation of the laser and the optimization of the application environment.

The invention discloses a clean room particulate matter monitoring system and method based on temperature field information, and relates to the field of intelligent monitoring. The system comprises an environment detection module used for detecting real-time air parameters of a detected environment; the environment purification module is used for purifying the air of the detected environment; the motion module is used for moving the environment detection module and the environment purification module to a designated position according to an inspection instruction, and the inspection instruction comprises an inspection path or / and a temperature gradient change instruction; the control module is used for controlling the environment detection module, the environment purification module and the movement module; according to the invention, the newly found abnormal area can be intelligently planned and automatically incorporated into the existing inspection route, so that the robot can maintain the high efficiency of fixed path inspection, the autonomous and intelligent identification and dynamic path optimization capabilities are remarkably improved, the overall workload and detection time are greatly reduced, and the inspection efficiency is improved. And the monitoring efficiency and accuracy of the particulate matters in the clean room and the intelligent level of long-term maintenance are obviously improved.

The embodiment of the utility model provides a single battery and a battery pack. The single battery comprises a battery cell, a shell, an anti-explosion valve and a filtering structure, the battery cell is arranged in the shell; the shell is provided with a mounting hole, and the anti-explosion valve is arranged in the mounting hole; the filtering structure is arranged outside the shell and at least covers the anti-explosion valve, the filtering structure comprises at least two layers of filter screens, and the filter screens are used for intercepting particulate matter in the flue gas. By arranging the filtering structure, particulate matters discharged during pressure relief of the anti-explosion valve can be effectively intercepted, so that the particulate matters are prevented from being splashed to other single batteries without thermal runaway to cause thermal runaway, and the use safety of the single batteries is favorably improved.

The invention belongs to the technical field of coating equipment, particularly relates to a chamber gas inlet pipeline and gas flow uniformizing structure of PECVD (Plasma Enhanced Chemical Vapor Deposition) equipment, and aims to solve the problems that the dispersion concentration of dissociated chamber gas of the existing PECVD equipment is non-uniform, the gas concentration close to the inlet end of a gas pipeline exceeds that of other areas, and the gas flow uniformizing structure is not uniform. In order to solve the problems that the plasma concentration is too high in the part of film forming process, the phenomenon that particulate matter is gathered on half and exceeds the standard is caused, and meanwhile the uniformity of final film forming becomes poor due to the fact that the plasma concentration is inconsistent in the film forming process, the following scheme is provided that an air inlet cavity is included. The chamber gas inlet pipeline and the gas flow uniformizing structure of the PECVD equipment disclosed by the invention can assist the gas flow uniformizing plate I and the gas flow uniformizing plate II in diffusing gas introduced from the center above the chamber to the periphery; the risk that particulate matter exceeds the standard due to uneven concentration dispersion of single-pipeline gas inlet is avoided through secondary flow uniformizing of the first gas flow uniformizing plate and the second gas flow uniformizing plate, and the added secondary flow uniformizing can further improve the uniformity of the membrane.

The invention belongs to the technical field of atmospheric environment monitoring, and particularly relates to an unmanned aerial vehicle laser radar calibration quality control system and method, and the system comprises an unmanned aerial vehicle flight platform, a laser radar module, a navigation positioning module, a control communication module, a data processing module and a ground station. The unmanned aerial vehicle flying platform comprises a shockproof holder and a protective pod; the laser radar module comprises a laser radar, a scanner module and a photoelectric detector module. According to the invention, one unmanned aerial vehicle is adopted to carry various different types of laser radars, the extinction coefficient is measured by combining optical beam splitting, signal processing and algorithm inversion technologies, and atmospheric particulate classification is effectively monitored through cooperation of a high-precision optical system and an algorithm; the extinction coefficient and the depolarization ratio work cooperatively, high-precision quantitative analysis and classification of pollutants can be achieved, the combined measurement function of the extinction coefficient and the depolarization ratio is achieved, and high-resolution three-dimensional monitoring of atmospheric particulates is achieved through multi-parameter cooperative inversion of the laser radar.

The invention provides an inert gas generation system, and relates to the technical field of industrial gas production. The inert gas generation system comprises the following modules: a gas pretreatment module, an intelligent separation module, a dynamic purification module, a pressure regulation and control module, a quality analysis module, a safety control module and an energy efficiency optimization module, and the gas pretreatment module is used for removing particulate matters through an electrostatic dust collection device by adopting a multi-stage gradient filtering algorithm based on ambient air input, adjusting humidity by combining a dew point control technology, forming a standardized gas source and generating a standard gas source. Through combination of a multi-stage gradient filtering algorithm and a dew point control technology, collaborative treatment of particulate matters and humidity is realized, stable gas source input is formed, the reliability of a subsequent processing link is improved, membrane separation parameters are dynamically predicted by applying a convolutional neural network model, and the permeation efficiency of a hollow fiber membrane stack is optimized.