496 results about "Material analysis" patented technology

The invention relates to the technical field of image processing, and discloses a graphite composite insulation board production process control method and system and a storage medium. The control method comprises the following steps: carrying out characteristic analysis and proportion optimization on raw materials to obtain pretreated raw materials; and monitoring the reaction state of the pretreated raw material, regulating process parameters, and generating a modified raw material. And performing formula optimization and performance prediction based on the material parameters of the modified raw material to obtain an optimized formula material. And forming process parameters of the optimized formula material are analyzed, a forming process is regulated and controlled, and a forming material is generated. And the curing process is optimized through the state parameters of the forming material, and a cured product is formed. And finally, evaluating the quality according to the detection data of the cured product, and generating a production control scheme. By establishing a multi-dimensional data acquisition and processing system, intelligent control over the whole production process is achieved, and therefore the stability and consistency of product quality are improved.

The invention discloses a slope stability evaluation method based on micro-seismic signal double-dominant-frequency mechanism characteristics, and relates to material analysis and application. The method is based on the objective principle that rock acoustic emission dominant frequency characteristics and micro-seismic signal dominant frequency characteristics have consistency and relevance, and the phenomenon of double dominant frequency characteristics existing in acoustic emission tests and micro-seismic monitoring. A rock sample dominant frequency characteristic rule obtained by an acoustic emission test is used for processing micro-seismic signal waveform data obtained by micro-seismic monitoring, so that a dominant frequency characteristic evolution rule of slope rock damage can be obtained through a micro-seismic signal, and the stress condition of the slope rock is more accurately judged based on the dominant frequency characteristic evolution rule; the stability of the slope is evaluated, so that the accuracy of an evaluation result is remarkably improved; the evaluation method combines an acoustic emission test and micro-seismic monitoring, has the advantages of high evaluation accuracy and good universality, and is suitable for large-scale application in monitoring and prevention of geological disasters such as landslide and the like.

The invention provides a double-space fatigue electron microscope test system, which is applied to the technical field of material analysis, and comprises an electron microscope module, a fatigue loading module and a vacuum isolation damping module, the vacuum isolation damping module controls two spaces of the electron microscope module and the fatigue loading module to be communicated or independent; the fatigue loading module comprises a hydraulic loading actuator, an electromechanical loading actuator, a loading rod and a fixing clamp, the fixing clamp is used for clamping a to-be-tested sample, and the loading rod is used for stretching or extruding the to-be-tested sample; and the fatigue loading module is driven by the moving mechanism to reciprocate along the X axis to adjust the position of the to-be-tested sample or rotate along the X axis to realize switching of different stations. According to the double-space fatigue electron microscope test system, combined use or independent use of the electron microscope module and the fatigue loading module is realized, and adverse factors such as vibration and pulse generated by the fatigue loading module during electron microscope observation are improved; in-situ compensation is achieved by means of cooperation of loading force and displacement of the fatigue loading module, and the observation effect of the electron microscope is improved.

The invention discloses a path planning method for a palletizing robot based on a multi-path convolutional neural network, and relates to the technical field of convolutional neural networks, and the method comprises the steps: employing the three-source data of a quality inspection report image, a damaged video and a microscopic image, extracting features through a parallel convolutional neural network, generating a dynamic maximum curvature constraint value after the fusion, and obtaining the path planning of the palletizing robot. And self-adaptive path planning of material characteristics is realized. And nodes conforming to curvature constraint are screened based on a probability route map (PRM) to generate a track, and the vibration spectrum energy of the mechanical arm is monitored in real time. When vibration exceeds a dynamic safety threshold value, subsequent path constraint is tightened in real time through a curvature penalty factor, and the damage risk is reduced by 90%; a closed loop of material analysis, path generation, vibration feedback and parameter correction is established, and balance of safety and efficiency is achieved in a high-speed stacking scene.

The invention discloses a high-precision dynamic sensing method for coarse-grain-size dam materials based on 5G and visual intelligence, and the method comprises the steps: setting a 5G base station or 5G access equipment in a dam region, and collecting dam surface image data through employing an unmanned plane; transmitting the acquired image data in real time through a 5G network; a database server and an image processing server are arranged on the ground, and the database server receives and stores collected data through a 5G network; a dam material analysis model constructed based on a YOLOv8 model is arranged in the image processing server; the image data in the database server is called by the cloud server and input into a dam material analysis model, and the dam material analysis model calculates the particle size of stones and aggregates by adopting a minimum bounding rectangle method based on an instance segmentation result of a YOLOv8 model, and identifies oversized stones, oversized aggregates and the position and area of a concentrated region of the oversized stones and the oversized aggregates; and the image processing result is sent to the database server for storage by the image processing server. According to the invention, the labor is reduced and the detection efficiency is improved.

The invention relates to a double-spectrum target detection method based on physical prior constraints, and belongs to the technical field of computer vision and deep learning. The method comprises the following steps: acquiring an RGB image and an IR image after registration, and extracting RGB and IR global feature vectors; constructing a double-spectrum target detection model by adopting a double-branch convolutional neural network; carrying out physical constraint fusion on the RGB and IR features to construct a bimodal fusion feature vector and training a model; wherein the model comprises a double-branch backbone network, a physical prior constraint module, a physical fusion module, a physical enhancement UNet module and a multi-scale detection head; the thermal physical constraint module establishes temperature-radiation relation constraint based on Stefan-Boltzmann law, the material analysis module identifies 12 materials and establishes physical attribute mapping, and the physical consistency verification module performs sub-pixel level registration and multi-level consistency detection; a to-be-detected image is collected and input into the trained model to obtain a detection result. According to the invention, high-precision rapid nondestructive detection of a target in a complex environment is realized.

The invention provides a method and system for calculating the ultra-high cycle fatigue life of a wind power blade in a complex environment, and relates to the technical field of material analysis and evaluation.The method comprises the steps that a wind power blade sample is collected, environmental parameters such as humidity, wind speed and salt mist concentration are set, and the influence of the marine environment on the wind power blade is simulated; performing a simulation test, establishing a relationship among the humidity, the wind speed, the salt mist concentration and the salt mist corrosion load, and calculating corresponding influence coefficients and influence constants; and applying different salt spray corrosion loads to the wind power blade sample by utilizing finite element analysis, respectively obtaining time-stress relation curves under different environmental parameters, measuring limit stress, and taking the time for reaching the limit stress as the fatigue life. And finally, comprehensive fatigue life evaluation of the wind power blade in the complex marine environment is generated by integrating the fatigue life under the influence of each environmental parameter.

The invention relates to the technical field of advertisement putting methods, in particular to an information flow advertisement module putting method, which specifically comprises the following steps of: 1, constructing a user portrait, collecting and analyzing behavior data of a user on various platforms, and constructing the user portrait; 2, analyzing and classifying advertisement materials; step 3, selecting and evaluating a delivery platform, namely selecting a corresponding delivery platform and evaluating the delivery platform; step 4, making a putting strategy, and making a specific putting strategy according to a user portrait, advertisement material classification and a putting platform evaluation result; 5, real-time monitoring and data collection: in the advertisement putting process, monitoring the advertisement putting effect in real time and collecting related data; according to the method and the device, the advertisement putting accuracy can be improved, an advertiser can accurately reach a target customer group, and the click rate and the conversion rate are improved.

The invention relates to the technical field of material analysis, and discloses an intelligent raw material composition screening method and system based on a sound insulation material, and the method comprises the steps: collecting acoustic characteristic test data, microstructure data and chemical composition data of a candidate sound insulation material; performing frequency response curve decomposition on the acoustic characteristic test data to obtain a characteristic frequency band sound absorption coefficient, and constructing an acoustic impedance tensor of the sound insulation material to analyze the sound wave dissipation performance of the candidate sound insulation material; calculating the pore distribution entropy and connectivity index of the candidate sound insulation material to analyze the sound wave propagation retardation efficiency of the candidate sound insulation material; analyzing the molecular chain flexibility and interfacial compatibility of the candidate sound insulation material to evaluate the acoustic performance stability of the candidate sound insulation material for multi-component compounding; and screening a target material from the candidate sound insulation materials by using sound wave dissipation performance, sound wave propagation retardation efficiency and acoustic performance stability. The performance matching degree of the raw materials screened out of the sound insulation material in actual composite use can be improved.

The invention relates to the technical field of material analysis, in particular to a crystal plasticity finite element modeling method, a crystal plasticity finite element modeling device, a storage medium and electronic equipment. The crystal plasticity finite element modeling method comprises the following steps: collecting grain information of a given material sample; performing crystal grain division based on the crystal grain information to obtain a crystal grain data file, and determining grid parameters based on a crystal grain with a minimum crystal grain morphology area in the crystal grain information; creating a grain geometric model according to the grain data file, creating a grid model according to the grid parameters, and mapping the grain geometric model to the grid model to obtain a crystal plasticity finite element grid model; and endowing a boundary condition and a constitutive relation to the crystal plasticity finite element mesh model so as to realize crystal plasticity finite element simulation. According to the crystal plasticity finite element modeling method provided by the invention, the modeling calculation efficiency can be improved while the model precision is ensured.

The invention discloses an inorganic solid material analysis system and method, and relates to the technical field of material analysis, the inorganic solid material analysis system comprises an oxygen-nitrogen-hydrogen analyzer, a first robot, a second robot, a sample preparation clamp, a sample preparation driving device, a deoiling container, an air blower, a sample disc, a cleaning dust removal assembly and a controller; the first robot can insert one end of a rough blank of a to-be-processed sample into the sample preparation clamp, and the first robot can take out the to-be-analyzed sample from the deoiling container, move the to-be-analyzed sample to the air blower and place the to-be-analyzed sample into the sample disc; the second robot can take out a to-be-analyzed sample from the sample disc and put the to-be-analyzed sample into the oxygen-nitrogen-hydrogen analyzer, the second robot can move away an old crucible on a lower electrode of the oxygen-nitrogen-hydrogen analyzer, and the second robot can move the cleaning and dust removing assembly into a hearth or the lower electrode of the oxygen-nitrogen-hydrogen analyzer; the second robot can place the new crucible on a lower electrode of the oxygen-nitrogen-hydrogen analyzer; according to the invention, manpower can be effectively saved, and personnel safety is ensured.

In one aspect, the present disclosure relates to a material analysis method which may comprise the steps of: (a) preparing a specimen for structure analysis; (b) training an artificial intelligence model with a training image labelled with a structure aspect of an arbitrary specimen; (c) analyzing a plurality of analysis images not labelled with a structure aspect of a specimen using the trained artificial intelligence model, and removing analysis images classified into preset noise structure aspects; and (d) analyzing, by using the trained artificial intelligence model, the analysis images from which the analysis images classified into the noise structure aspects have been removed, and classifying the analysis images into at least one target structure aspect.

The invention relates to the technical field of material analysis, in particular to a method for evaluating a pore structure of a refractory material by using industrial CT, which comprises the following steps: selecting an X-ray source parameter, a detector parameter, a focal length and the like of the industrial CT to be matched with a refractory material with different thicknesses, selecting a filter to avoid image noise, identifying an internal structure of the refractory material, and evaluating the pore structure of the refractory material. And obtaining a two-dimensional projection image of the internal structure. According to the method, the image noise is reduced through the filtering technology, the internal structure of the refractory material can be identified more accurately, the data integrity is ensured, a more accurate three-dimensional model can be generated, the analysis of the pore structure is more detailed and accurate, and by quantitatively analyzing the pore size, shape and distribution of the refractory material, the analysis accuracy of the refractory material is improved. The performance change of the material can be effectively monitored, the prediction capability of the refractory material in practical application is improved, and the application safety and reliability of the refractory material in an extreme environment are enhanced.

The invention relates to the technical field of medicinal liquor stability enhancement, and discloses a long-noded pit viper medicinal liquor stability enhancement system. Comprising a raw material monitoring module, a substance analysis module, a stability prediction module, a phase change correction module and a dispersion spectrum optimization module. The raw material monitoring module collects data through preprocessing nodes and a dynamic proportioning network and constructs a multi-stage raw material fusion topology; the substance analysis module analyzes components and inhibits precipitation by using a spectrum analysis unit and a precipitation inhibition unit; the stability prediction module generates a stability strategy through a turbidity modeling node and a colloid optimization unit, and optimizes a dispersion state; the phase change correction module corrects a phase state and calibrates parameters by means of a temperature isolation unit and an oscillation compensation unit; and the dispersion spectrum optimization module constructs an evaluation network to monitor the settlement rate and feeds back and adjusts the settlement rate. According to the system, real-time monitoring, dynamic analysis and accurate regulation and control of the stability of long-noded pit viper medicinal liquor are realized, the component balance of the medicinal liquor is improved, the generation of precipitates is inhibited, the environmental adaptability is enhanced, and the stable product quality is guaranteed.

The invention relates to the technical field of material analysis, and particularly discloses an ICP-AES (Inductively Coupled Plasma-Atomic Emission Spectrometry)-based automatic quantitative analysis method for primary and secondary elements in a high-temperature alloy, which comprises the following steps: dissolving a to-be-analyzed high-temperature alloy sample in a mixed acid of sulfuric acid and nitric acid to obtain a to-be-detected sample solution; feeding the sample solution to be detected into an atomizing chamber through a peristaltic pump, and collecting emission spectrum data of each element; establishing a standard curve of the concentration and emission intensity of each element by using a standard solution with known concentration; pre-processing the received emission spectrum data through a control system and a data processing module of the instrument; the data processing module compares the preprocessed emission spectrum data with a standard curve through a multiple linear regression method; and generating a detailed analysis report, and transmitting the generated analysis report to terminal equipment of a user through a printer or a network. Through an optimized sample dissolving method, a data preprocessing technology and a real-time correction algorithm, the accuracy and the stability of an analysis result can be effectively improved.

The invention relates to the technical field of hydraulic building material analysis, in particular to a material performance analysis method based on dam material physical properties and a related product, and the method comprises the following steps: applying multi-physical field composite loading including water pressure and temperature change to a sample of a dam material, collecting multiple performance data of the test sample in the composite loading process; key indexes are extracted according to the performance data; a comprehensive performance evaluation model is constructed based on the key indexes, an evaluation value representing the comprehensive performance of the dam material is obtained through calculation, and quantitative comprehensive analysis on the performance of the dam material is completed; according to the method, the performance comprehensive evaluation model integrating the core indexes is constructed, a principal component analysis and self-learning mechanism is introduced, and automatic extraction of main factors, reasonable weight distribution and dynamic adaptation of the regional environment are realized on the basis of original performance data; and the problems of single-point data isolation, weak coupling capability, poor structure specificity and the like in a traditional evaluation method are obviously solved.

The invention discloses an intellectual property achievement transformation management system, and relates to the technical field of intellectual property management systems, comprising the following steps: S1, storing intellectual property materials; s2, material analysis; s3, feature extraction: carrying out keyword automatic extraction by utilizing a big data patent file, forming a keyword set, carrying out position analysis on a text of the patent file, marking a word segmentation sequence, inserting a user dictionary, recording related proper nouns of the technical field to which the patent file belongs, filtering stop words and virtual words in the text of the patent file, and carrying out feature extraction; calculating and counting feature items in the patent document text; and S4, website display. According to the method, the optimal patent with relatively high matching degree with the demand of the enterprise user can be conveniently provided for the enterprise user, one-time sorting can be performed according to the matching degree, the value degree of multiple patents can be judged at the same time, the rate that the user needs to use keywords to perform knowledge library knowledge retrieval is improved, meanwhile, the scientific and technological achievement conversion efficiency can be improved, and the enterprise user experience is improved. And enterprises can select conveniently.

The invention relates to the technical field of material analysis, in particular to an intelligent inspection device and method for bridge structure diseases, and the method comprises the steps: determining a plurality of disease suspected regions through obtaining a plurality of frames of unmanned aerial vehicle images of a bridge structure, carrying out the feature analysis of each disease suspected region, and determining the feature value of each disease suspected region; according to different candidate time interval lengths and characteristic values, determining interval change fluctuation degrees representing the possibility of rain and sewage flow marks corresponding to different candidate time intervals in each disease suspected area, and carrying out feature distinguishing on the rain and sewage flow marks and crack diseases; according to the interval change fluctuation degree, determining interval division fitness, comprehensive identification capability and timeliness of different candidate time intervals; according to the interval division fitness, the target interval change fluctuation degree corresponding to each disease suspected area is determined, so that the crack disease area is determined for intelligent inspection, the recognition accuracy is improved, and the intelligent inspection effect is ensured.

The invention relates to the technical field of material analysis, in particular to a rare earth element online detection device and method based on laser-induced breakdown spectroscopy. According to the invention, the laminar flow lining plate is arranged, and the to-be-detected liquid is conveyed to the laminar flow lining plate through the liquid conveying device, so that the laminar flow of the to-be-detected liquid is formed on the laminar flow lining plate. Then, an LIBS signal of the to-be-detected liquid laminar flow is collected through an LIBS signal collection device, and the to-be-detected liquid laminar flow can reduce laser energy consumed by solvent evaporation, so that the signal intensity is improved; and the to-be-detected liquid laminar flow can also reduce the fluctuation of the liquid level, so that the signal stability is improved. In addition, the acoustic signal of the liquid laminar flow to be detected is acquired through the acoustic signal acquisition device, and the LIBS signal and the acoustic signal are jointly analyzed, so that the accuracy of rare earth element detection can be improved.

The invention relates to a method for determining impurity elements in zirconium oxide, in particular to a method for determining impurity elements in high-purity zirconium oxide through direct current glow discharge mass spectrometry. The method meets the requirements of modern high-purity material analysis and test on reliability, accuracy and multi-element rapid analysis.

The invention relates to the technical field of material analysis, in particular to a light microscope-field emission electron microscope combined shale rock slice analysis and identification method, which comprises the following steps of: firstly, combining a brightness distribution condition represented by a bright field image of a shale rock slice and a birefringence deviation condition represented by a cross polarization image from an optical angle; determining a mineral discrimination index representing an atomic number agent; applying offsets of different sizes based on the distribution condition of mineral discrimination indexes and the surface fluctuation condition of shale rock slices, and determining a position offset vector by combining gray scale gradient distribution on the basis; and finally, determining the cross-scale positioning and more accurate electron microscope objective table coordinates corresponding to each pixel point in combination with a position offset vector in a pixel coordinate conversion process based on an image physical distance scale and rotation translation processing, so that the cross-scale positioning accuracy of the optical microscope and the field emission scanning electron microscope is higher. The reliability of analyzing and identifying the shale rock slice is obviously improved.

The invention discloses a testing device and an analysis method for gas adsorption and desorption behaviors of a porous material. The testing device comprises an infrared spectrometer; a gas adsorption instrument; the temperature controller is connected with the infrared spectrometer; the nitrogen generator is connected with the infrared spectrometer; the cooling-water machine is connected with the infrared spectrometer; the liquid nitrogen tank is connected with the infrared spectrometer; the two ends of the connecting pipe are connected to the infrared spectrometer and the gas adsorption instrument respectively, and a second gas inlet valve is arranged on the connecting pipe and used for controlling on-off; and the connecting pipe is coated with a heating belt. The gas molecular state and the dynamic behavior can be detected and analyzed through the infrared spectrometer, the gas temperature can be controlled through the temperature controller, the cooling-water machine, the liquid nitrogen tank and the heating belt, nitrogen is output through the nitrogen generator to maintain the internal gas environment of the infrared spectrometer, and environmental interference is reduced. The invention relates to the technical field of porous material analysis equipment.

The invention discloses a metal JC constitutive model parameter optimization method for metal material analysis, which comprises the following steps of: rearranging and combining experimental data from different sources according to different quantities to describe the influence of the experimental quantity on the uncertainty of JC constitutive model parameters, and wrapping all possible JC constitutive model parameters; according to the method, the uncertainty range of model parameters can be completely described, the uncertainty representation of the current JC constitutive model parameters is obtained by calculating the basic inference allocation, namely, the BBA value, of each interval, the complete JC constitutive model parameter uncertainty representation can be obtained by fusing the JC constitutive model parameters of multiple data sources, and a model with the JC constitutive model parameters as input and the BBA value as output is established. According to the method, a JC constitutive model uncertainty transfer method is established by taking the response of the metal structure as an output proxy model, the calculation amount required by parameter updating is reduced, and the updating of the parameters of the JC constitutive model is completed through the real response of the metal structure in an experiment.

The invention relates to the technical field of material table robots, in particular to an intelligent material table robot system based on an AI vision technology, which is provided with a material table control module, a feature acquisition module, a material analysis module, a material identification module and a grabbing regulation and control module, a material analysis module determines the gray fluctuation condition of to-be-sorted materials according to gray characterization parameters in a grabbed recognition area at different illumination angles so as to mark the feature grabbed recognition area, a material recognition module determines a shielding trend sub-area, a shielding trend sub-vector is constructed, and the shielding trend sub-vector is calculated. And a grabbing compensation mode of the to-be-sorted materials is determined through a grabbing regulation and control module according to the comparison condition of the conveying direction vector and the shielding trend vector. According to the method, the grabbing recognition area with shielding interference is marked according to the gray features of the materials, the grabbing compensation mode is adaptively adjusted based on the change trend of dynamic shielding, and the efficiency and reliability of an intelligent material table robot system are improved.

The invention relates to a testing device for chemical material analysis, which comprises a base, a puncture needle, a pressure sensor, a tension sensor and a clamp, the clamp comprises an upper clamping plate and a lower clamping plate which are identical in shape and size, and the upper clamping plate and the lower clamping plate are provided with puncture holes for the puncture needle to penetrate through. The upper clamping plate and the lower clamping plate respectively comprise two semicircular clamping plates, and the two semicircular clamping plates which correspond to each other up and down are detachably and fixedly connected; a lifting plate is connected to the base in a lifting mode, the puncture needle is vertically arranged on the lifting plate, the pressure sensor is arranged between the lifting plate and the puncture needle, two driving blocks are arranged at the lower ends of the two semicircular clamping plates of the lower clamping plate, and the tension sensor is arranged between the driving blocks and the semicircular clamping plates. According to the invention, the tensile strength test and the puncture strength test can be integrated on the same sample, so that the sample material is saved, the assembling and disassembling steps of the clamp are reduced, and the integration and automation of the whole test are facilitated.

According to the technical scheme, the method for image analysis through combination of the metallographic microscope and the AI comprises the steps of hardware preparation, software development, data acquisition and processing, model training and optimization, system integration and testing and application and optimization. According to the system integration and test, a microscope, an automatic platform, image acquisition and processing software, an AI model and the like are integrated into a complete system, smooth communication and cooperative work among components are ensured, and comprehensive system test is carried out. The method has the advantages that the AI is used for automatically identifying and analyzing the microscopic image, the manual operation time is greatly shortened, meanwhile, the AI model can provide a high-precision and consistent analysis result through mass data training, a large amount of microscopic image data is processed and analyzed through a big data platform, and the accuracy of the analysis result is improved. Valuable rules and modes can be mined from mass data, and the depth and breadth of material analysis are improved.

The invention discloses a method for preparing a section sample of a new energy automobile battery powder material, and relates to the technical field of battery material analysis, and the method comprises the following steps: uniformly mixing a battery powder material with a liquid conductive adhesive solution; pouring the mixture into a mold for curing, and demolding to obtain a conductive sample block with a regular shape; directly loading the conductive sample block in an ion beam cutting system for ion cutting to obtain a flat sample section; and surface metal spraying treatment is not needed, and electron microscope observation and analysis are directly carried out. According to the preparation method, the conductive adhesive solution is adopted for inlaying and is combined with mold forming, so that time-consuming mechanical grinding and polishing procedures in a traditional method are omitted, and the preparation period is greatly shortened; and meanwhile, an in-situ conductive network formed after the glue solution is cured is utilized to effectively inhibit the charge effect, so that direct observation without metal spraying is realized, sample preparation damage and plating interference are avoided, and the authenticity and accuracy of an analysis result are ensured. The method is simple and convenient to operate and good in repeatability.

The invention provides an asphalt mixture damage assessment method and device based on an acoustic emission technology, and relates to the field of asphalt material analysis. The method comprises the following steps: acquiring a target asphalt mixture sample; obtaining corresponding load-displacement data through a semicircular bending test; acoustic emission data of the target asphalt mixture sample under semicircular bending test loading are obtained through acoustic emission nondestructive testing; based on the load-displacement data and the acoustic emission data, constructing a target image corresponding to the target asphalt mixture sample; according to the target image, obtaining interface damage characteristics corresponding to the target asphalt mixture sample; and inputting the interface damage characteristics into a statistical damage constitutive model, and outputting a damage assessment result corresponding to the target asphalt mixture sample through the statistical damage constitutive model. The problem that a damage detection method based on appearance observation and physical testing cannot accurately detect and evaluate the damage state of the asphalt pavement is solved.

The invention discloses a security check image recognition and early warning system based on a terahertz imaging technology, relates to the technical field of security check image recognition and early warning, and solves the technical problems that in the prior art, linear change processing cannot be carried out on a terahertz image, the availability of the image cannot be ensured, and consequently the subsequent article comparison efficiency is reduced. The terahertz imaging control unit is used for carrying out region division according to a real-time security check execution region and carrying out terahertz imaging mode control according to the divided region; the material analysis unit is used for performing material analysis on the object detected in real time in the terahertz image, and determining the material of the corresponding detected object in the terahertz image by combining terahertz image analysis with wavelength transmission process analysis of an imaging technology in an actual scene; and the terahertz image processing unit is used for carrying out linear change processing on the terahertz image, adjusting the gray level distribution condition of the image by establishing gray level mapping, and improving the definition of the image.

The invention discloses a salt spray test device for simulating a salt spray environment, and relates to the technical field of material analysis equipment. The device comprises a main box body, a box cover, an ultrasonic salt mist generating device, an axial flow fan, an airflow distributor, an airflow guide device, a salt mist metering device, a control device panel and the like, wherein the main box body is provided with an inner cavity and a top sealing water tank; an auxiliary box body is arranged on one side of the main box body, and the auxiliary box body is provided with an inner cavity and is communicated with the inner cavity of the main box body; the upper end of the auxiliary box body is provided with a sunken saline water tank for storing saline water; the bottom of the ultrasonic salt mist generating device is communicated with the salt water tank through a conduit. Through the innovative structure, many problems of a traditional test are solved, salt mist distribution is optimized, and uniformity is ensured; temperature and humidity are accurately controlled, and simulation is more real; an ultraviolet light source is introduced, the illumination period is precisely regulated and controlled, and the device fits the natural environment; the corrosion resistance of the material can be comprehensively and accurately evaluated, reliable test support is provided for research, development and application of the material, and product quality and reliability are improved.