3100results about "Investigating material hardness" patented technology

The invention discloses a wharf armor block quality detection method, and belongs to the technical field of concrete structure detection.The method comprises the steps that a surface model is constructed through a movable three-dimensional laser scanning device, and a high-risk defect area is recognized; performing encryption scanning and impact echo detection in the high-risk area by adopting a frequency-adjustable dual-mode flaw detection device to generate a three-dimensional defect distribution diagram; a core sample is drilled in the defect area for compressive strength testing, and the material performance is analyzed in combination with a non-contact infrared spectrum; and establishing a dynamic evaluation model, calculating a safety coefficient by integrating surface defects, internal defects and material discreteness data, and generating a three-dimensional visual report. The problems that a traditional detection method is low in efficiency, insufficient in internal defect positioning precision, one-sided in material performance evaluation and the like are solved, full-dimensional detection from the surface to the interior and from the macroscopic level to the microscopic level is achieved through a multi-source data fusion and closed-loop feedback mechanism, and the reliability of structural safety evaluation and the scientificity of maintenance decision are remarkably improved.

The invention relates to the technical field of concrete detection, in particular to a dynamic detection and analysis method and system for early performance of ultra-high performance concrete. According to the technical scheme, the method comprises the steps of establishing a raw material characteristic spectrum library based on multi-physics field coupling, constructing a dynamic detection array based on a time sequence, developing a multi-modal data fusion algorithm, establishing a nonlinear coupling effect decomposition model and implementing dynamic parameter inversion. According to the method, a technical chain of four-dimensional monitoring network-multi-physics field coupling analysis-cross-scale prediction-adaptive regulation and control is constructed, so that dynamic accurate detection and intelligent regulation and control of the early performance of the ultra-high performance concrete are realized, and the technical bottlenecks of a traditional method in the aspects of parameter coupling, cross-scale association and real-time regulation and control are solved; the early performance prediction precision and the maintenance efficiency are remarkably improved, the cracking risk is reduced, and reliable technical support is provided for application of the ultra-high performance concrete in major engineering.

The invention discloses a health assessment method for a long-distance underground culvert structure, and the method comprises the steps: carrying out the fusion processing based on acoustic and optical detection data, so as to recognize a structure defect; based on underwater rebound and coring test data, carrying out underwater-dry conversion and correction on a strength value, and determining corrected structural strength and material degradation parameters; in combination with defect, degradation and historical monitoring data, carrying out structure evolution modeling and mutation risk identification to obtain evolution characteristics and mutation risks of the structure; and integrating the corrected structural strength, evolution characteristics and abrupt change risks, performing full-field state assessment, and generating a structural health assessment and risk early warning result. According to the method, accurate, dynamic and full-field evaluation of the health state of the culvert can be realized, and the reliability and early warning capability of an evaluation result are improved.

The invention discloses a copper extraction effect analysis method and system, and the method comprises the steps: carrying out the continuous scanning of the surface of a copper sample through an optical sensor, and obtaining the chromaticity change time sequence data in a refining process; and carrying out segmentation processing on the data by utilizing a preset threshold value, and extracting dynamic change trend characteristics and key point locations. And in combination with conductivity and hardness value data recorded by a real-time monitoring system, a polynomial regression model is constructed, and correlation between copper purity and physical characteristics is established. And through historical data calibration and mean filtering optimization, the mapping relation between chromaticity change and copper purity is determined. And finally, according to the optimized chromaticity characteristic value and the calibrated correlation model, calculating the quantitative score of the real-time refining effect, and judging the grading basis of the copper purity. According to the method, the real-time evaluation of the copper purity and the dynamic optimization of the refining process are realized, and the refining efficiency and the product quality are improved.

The invention relates to the technical field of livestock breeding, in particular to a cow manure automatic scoring system and method.The cow manure automatic scoring system comprises an image acquisition unit, a physical property sensor, a chemical component detection module and a data processing unit.The image acquisition unit is used for capturing the form, color and fiber residue of manure; the physical property sensor is used for measuring the water content of excrement and evaluating the viscosity and hardness of the excrement; the chemical component detection module comprises a near infrared spectrum analysis unit and an electrochemical sensor unit; and the data processing unit is used for integrating an AI algorithm, realizing multi-source data fusion and scoring, and uploading the data to the cloud management platform through the communication module. Therefore, the problems that in the prior art, manual scoring is subjective, low in efficiency and difficult to quantify, diseases are difficult to find early due to the lack of rapid component detection means, and accurate nutrition regulation and control are difficult to achieve due to the fact that scoring data are difficult to integrate into a breeding system are solved.

The invention discloses a rock mechanical parameter determination method based on a nanoindentation experiment, which comprises the following steps: S1, randomly selecting a small part of a target rock to carry out the nanoindentation experiment, and testing the elastic modulus, hardness and fracture toughness micromechanical parameters of the target rock; s2, constructing a multi-scale structure model of the target rock by considering internal cracks, pores, organic matters and proportion factors of each mineral component of the target rock based on the micromechanics parameters obtained by the nanoindentation experiment; s3, on the basis of the multi-scale structure model of the target rock, performing multi-scale transformation by utilizing a reformed group theory to obtain a simplified structure model of the target rock, and calculating mechanical parameters of the simplified structure model; and S4, carrying out a macromechanics experiment on the target rock, calculating mechanical parameters, and then checking the reliability of the method for calculating the mechanical parameters of the target rock based on the nanoindentation experiment. According to the method, the efficiency and precision of calculating the macromechanical parameters of the rock can be improved.

The invention relates to the technical field of concrete testing, in particular to a concrete testing method which comprises the following steps: manufacturing a plurality of groups of standard-size concrete test pieces according to a preset concrete mix proportion, and respectively placing the standard-size concrete test pieces under a simulated curing condition and a standard curing condition for curing in a preset curing period to form a first test group and a first control group; based on a plurality of detection points, carrying out a rebound test and an ultrasonic test on the concrete test pieces in the first test group, and determining a high-frequency ultrasonic section to determine an ultrasonic attenuation coefficient of a single concrete test piece, according to the ultrasonic propagation speed, the ultrasonic attenuation coefficient and the detection rebound value, constructing a concrete strength-based correction model to obtain the comprehensive compressive strength of the concrete test pieces in the first test group, and determining the standard compressive strength corresponding to the concrete test pieces in the first control group, and determining an initial influence coefficient of the simulated maintenance condition according to the comprehensive compressive strength and the standard compressive strength. The compressive strength of the concrete structure is effectively tested.

The invention discloses a cross-scale rock elastic mechanical parameter measurement method and system, and relates to the technical field of rock measurement, and the method comprises the following steps: obtaining nano-scale rock elastic mechanical parameters and micro elastic-plastic deformation of rock through a nanoindentation experiment, so as to construct a molecular dynamics model of the rock; according to the molecular dynamics model of the rock, using an inclusion homogenization theory to upgrade the rock elastic mechanics parameters of the nanoscale to the rock elastic mechanics parameters of the centimeter scale, so as to construct a rock elastic mechanics parameter conversion model, and using environmental data in an in-situ environment for correction; and inputting the nano-scale rock elastic mechanical parameters into the corrected rock elastic mechanical parameter conversion model to obtain centimeter-scale rock elastic mechanical parameters. According to the invention, centimeter-scale rock elastic mechanical parameters in a deep stratum in-situ environment can be accurately measured.

The invention provides a titanium plate performance analysis method and system, and relates to the technical field of metal material detection.The method comprises the steps that an optical scanner is adopted to establish a three-dimensional structure on the surface of a titanium plate, and test areas are divided; synchronously acquiring stress, hardness and conductivity data of a test point by using a multi-probe collaborative detection device; constructing a dual-branch feature extraction network, wherein the dual-branch feature extraction network comprises a surface topography feature branch and a physical feature branch; performing statistical integration on the features in the test area, calculating distribution features and determining a weight coefficient; and generating a performance analysis result through feature fusion and a multi-task output layer, and finally determining the performance grade of the titanium plate. According to the method, deep fusion of morphology information and physical characteristics is realized, and the accuracy and reliability of titanium plate performance evaluation are improved.

The invention provides a method and a device for evaluating and measuring microscopic mechanical properties of TC4 alloy, relates to the technical field of microscopic mechanical properties, and realizes accurate evaluation of material properties through combination of multi-scale characterization and numerical simulation. Firstly, a standard sample is prepared through selective laser melting, and residual stress field distribution is obtained through X-ray diffraction; dividing a stress field into sub-regions, and establishing a quantitative relationship between microscopic structure parameters and residual stress by combining SEM and EBSD analysis; the method comprises the following steps: acquiring local mechanical properties through a nanoindentation test, and constructing a stress-performance correlation model; and finally, establishing a finite element model, transmitting stress and tissue parameters by adopting trilinear interpolation and an inverse distance weighting method, verifying data reliability through a stress difference criterion, and calculating mechanical properties of each unit. According to the method, multi-scale correlation from microstructure characteristics to macroscopic mechanical properties is innovatively realized, so that the mechanical property distribution of the material is accurately evaluated.

The present invention relates to an in-situ micro-nano impact indentation testing instrument, falling within the technical field of material micromechanical testing. The instrument comprises a nitrogen generation module, an environmental chamber, a high / low temperature loading module, an “optical-infrared” in-situ monitoring module, an “electromagnetic-piezoelectric” coupling impact module, etc. After the nitrogen is introduced into the environmental chamber and the test area is determined by microscopic imaging, the “electromagnetic-piezoelectric” coupling impact module can drive an indenter to indent a specimen. An acoustic emission sensor embedded in the high / low temperature loading module can monitor the surface crack propagation of the specimen. The “optical-infrared” in-situ monitoring module can perform real-time high-speed optical imaging and infrared imaging on the impact indentation process. The present invention can perform micro-nano impact indentation testing on the material at high or low temperatures.

The invention provides an intelligent detection method for surface defects of a protective film based on machine vision, which comprises the following steps of: extracting stress concentration areas and touch signal attenuation characteristics from potential risks of touch response delay, and performing grouping analysis on the stress concentration areas and the touch signal attenuation characteristics, the combined attenuation trend of the optical transmittance and the touch signal attenuation is obtained; the deformation degree of the stress concentration area is recognized, the touch signal attenuation degree of the folding area is determined according to the combined attenuation trend of the optical transmittance and touch signal attenuation, and the durability of the folding screen is obtained through evaluation; and extracting early warning indexes about the screen curvature radius and the light scattering intensity defect from the attenuation trend prediction result, and generating a complete report containing the optical transmittance and the touch signal attenuation defect.

The invention provides a reservoir in-situ key rock mechanical parameter space inversion prediction method and a reservoir in-situ key rock mechanical parameter space inversion prediction system, and belongs to the field of shale oil and gas geology, and the reservoir in-situ key rock mechanical parameter space inversion prediction method specifically comprises the following steps: carrying out a nanoindentation experiment to obtain an indentation experiment database, and simulating rock indentation experiments under different conditions to obtain a macroscopic indentation numerical model; using a Latin hypercube sampling method to obtain a simulation parameter combination database, carrying out batch numerical experiments, and constructing an inversion data set; according to the inversion data set, training the deep neural network model subjected to Bayesian optimization to obtain a single-point inversion prediction model; further establishing a spatial inversion prediction model according to a Kriging interpolation algorithm; and inputting real-time detection data of the deep rock stratum into the spatial inversion prediction model to obtain real-time underground rock mechanical parameter spatial distribution data of the deep rock mass. The deep reservoir space key rock mechanical parameters can be accurately inverted, and a basis is provided for well spacing, well trajectory design, fracturing scheme optimization and the like.

The invention provides an ultrasonic rebound comprehensive detection method and system for bridge pier column concrete strength, and relates to the technical field of structure nondestructive testing, and the method comprises the following steps: obtaining ultrasonic propagation velocity data of a to-be-detected part of a bridge pier column; obtaining springback value data of a to-be-detected part of the bridge pier column; performing coupling processing on the ultrasonic propagation speed data and the rebound value data, and determining the concrete strength of the to-be-detected part by combining the pouring bedding direction of the bridge pier column concrete and the strength increasing coefficient corresponding to the curing age. And the accuracy and the stability of bridge pier column concrete strength detection are obviously improved.

The invention discloses equipment and a method for detecting the strength of an annular section of a large-diameter TA31 pipe, and relates to the technical field of pipes. According to the annular section strength detection equipment for the large-diameter TA31 pipe, through the design of a composite mechanism, the pipe is placed in the processing mechanism, the pipe space is restrained through the limiting mechanism, the pipe is prevented from moving in the inspection process, danger to workers is avoided, and therefore normal operation of the equipment is kept; the fixing mechanism controls the pipe to rotate and rub with the processing mechanism, so that the effect of cleaning the surface of the pipe is achieved, the situation that stains on the surface of the pipe affect the detection effect is avoided, a hydraulic rod controls a pressing plate to extrude the surface of the pipe, and the detection effect on the annular section strength of the pipe is achieved; therefore, the friction force on the surface of the pipe is increased, the pipe is prevented from shaking in the downward pressing process, and the operation stability is improved.

The invention provides a constructional engineering concrete compressive strength detection method and system.The method comprises the steps that multi-modal information of a to-be-detected concrete member for constructional engineering is collected, and the multi-modal information comprises rebound data, ultrasonic data, resistivity data and temperature data; constructing a hybrid prediction model; and outputting compressive strength data according to the mixed prediction model, and visually displaying the compressive strength data. According to the method and the system for detecting the compressive strength of the constructional engineering concrete, disclosed by the invention, multi-modal information such as ultrasonic, rebound, resistivity and temperature of the to-be-detected concrete member is input into the mixed prediction model for compressive strength prediction, and the model can be used for more accurately processing nonlinear and high-dimensional characteristics in data; a transfer learning mechanism is introduced, so that the model adapts to changes of different regions and materials under limited training data, and the generalization ability and accuracy of prediction are improved. And the compressive strength data is visually displayed, so that the analysis efficiency of engineers is improved.

The invention discloses a novel concrete pavement hardness detection device, and belongs to the technical field of detection. The invention discloses a novel concrete pavement hardness detection device, and belongs to the technical field of road engineering detection. The device comprises a springback tester, an ultrasonic tester and an analysis system, and equipment credibility parameters are generated through a springback confidence model (quantitative impact energy / angular deviation) and an ultrasonic confidence model (quantitative frequency / probe centering error); combining a pavement characteristic model (analyzing water content / temperature / steel bar density) to output an environment adaptation coefficient; further dynamically calculating a springback risk coefficient and an ultrasonic risk coefficient based on a risk model (fused vibration / carbonization depth); and finally, outputting a calibration intensity value through the intensity correction model. The method solves the defects of weak anti-interference capability and insufficient precision of a traditional method, effectively improves the detection efficiency, and is suitable for high-precision scenes such as expressways and airport runways.

The invention relates to the technical field of intelligent detection, and discloses a building quality evaluation method and system based on concrete nondestructive testing and a storage medium. The method comprises the steps that a piezoelectric ceramic sensor array is arranged to collect micro-vibration response signals, and an original vibration data set is obtained; extracting an energy distribution coefficient of each frequency band by using a wavelet packet decomposition algorithm, and constructing a damage feature vector matrix; establishing a physical constraint neural network model, and outputting a damage variable time sequence; fusing the damage variable with ultrasonic and rebound data, and calculating comprehensive strength and damage degree indexes; and calculating the remaining service life by using a time sequence prediction algorithm, and generating an evaluation report. According to the method, the technical problem that the existing concrete nondestructive testing technology cannot realize microstructure damage evolution dynamic monitoring and residual life prediction is solved, and the accuracy of building quality evaluation and the scientificity of predictive maintenance decision are improved.

The invention relates to a soil detection system and a detection method. Soil detection equipment comprises a sampling module, a positioning module for generating original point sampling coordinates, a sample treatment module for chemical, electrochemical and biological treatment means, a detection module, a detection database, a detection control module, a generating and sending module and a sending and receiving module. The detection method comprises the steps of sampling and processing, binding coordinates, comparing abnormal data through preliminary detection, generating a pollution map, carrying out secondary detection on abnormal data, calculating a spatial uncertainty index, dynamically generating a near-origin secondary sampling coordinate, circularly sampling and detecting until the index reaches the standard or the density upper limit, and finally generating the pollution map and a prediction model. And the detection database is updated and optimized through machine learning.

The invention relates to the technical field of concrete quality control, in particular to a concrete strength prediction system and method based on SVR. According to the invention, multi-dimensional data of rebound test, compressive strength test and carbonization depth value measurement are collected through the data acquisition module, rich input characteristics are provided for the model, and the prediction capability of the model is enhanced; and abnormal data is eliminated by adopting a Grubbs criterion, so that the quality and consistency of input data are ensured, and the influence of noise on model training is reduced. According to the method, a concrete rebound curved surface regression equation and a support vector regression model are established respectively and serve as prediction criteria, data fusion is carried out through a Kalman filter, and the prediction precision and reliability are further improved. Through automatic and standardized data processing procedures including data acquisition, preprocessing, regression prediction, SVR prediction, data fusion and the like, rapid prediction of the concrete strength is realized, and the prediction efficiency is improved.

The invention relates to a comprehensive performance verification method for a wear-resistant layer of a turbine blade, and belongs to the technical field of turbine blades, the comprehensive performance verification method comprises a melting performance test, a pressure-resistant performance test, a wear-resistant performance test, a high-temperature hardness test and a tension shear test, and the melting performance test is performed on a welding rod made of a first material; the first wear-resistant layer made of the first material is subjected to a pressure resistance test, the second wear-resistant layer and the third wear-resistant layer made of the first material are subjected to a wear resistance test, the fourth wear-resistant layer made of the first material is subjected to a high-temperature hardness test, and the blade crown wear-resistant layer made of the first material is subjected to a tension shear test. The device has the beneficial effects that a fusion performance test, a pressure resistance test, a wear resistance test, a high-temperature hardness test and a tension shear test are carried out on the welding rod made of the first material, so that the comprehensive performance test on the welding rod made of the first material is realized, and whether the welding rod made of the first material can be used for processing a blade or not is judged; and the machining quality and safety of the blade are ensured.

The technology provides a device that measures an internal structural integrity and surface hardness of baseball bats having a bat clamp that secures the baseball bat at a handle end, a bat support that secures the baseball bat at a barrel end, and a rebound hammer that impacts the baseball bat to determine a coefficient of restitution value. The rebound hammer may indirectly impact the baseball bat through a force dispersing tool. The technology further provides a device that measures vibration propagation within baseball bats, having a bat clamp that secures the baseball bat at a handle end, a vibration sensor provided proximate to the handle end, and a vibration impact tool that impacts the baseball bat to transfer a force thereto.

The invention relates to the technical field of titanium alloy detection, and discloses a titanium alloy wire performance detection method, equipment and system. The method comprises the following steps: acquiring real-time force value displacement data of a tensile test and echo signal data of ultrasonic detection, and processing to obtain smooth force value displacement data and spectrum characteristic parameters; performing feature layer fusion on the yield strength, the tensile strength, the peak frequency and the amplitude attenuation rate to construct a first multi-dimensional feature matrix; inputting a pre-trained deep belief network model, and predicting mechanical properties such as elongation and hardness value; and comparing with a preset threshold value, marking unqualified items and generating a detection report. According to the method, through multi-source data fusion and advanced algorithm processing, the comprehensiveness and accuracy of detection are improved, efficient evaluation of the performance of the titanium alloy wire is achieved, and the method is suitable for the strict detection requirements for the quality of the titanium alloy wire in the fields of aerospace, medical instruments and the like.

The application relates to the field of concrete testing, in particular to a concrete seamless floor strength testing device and an operating method thereof. The concrete seamless floor strength testing device comprises a mounting frame, a moving driving part one, a connecting table one and a dynamic rebound apparatus; the upper end of the mounting frame is provided with the moving driving part one; the driving end of the moving driving part one is provided with the connecting table one, and the moving driving part one controls the up-down movement of the connecting table one; three dynamic rebound apparatuses are arranged on the connecting table one; the device further comprises a moving driving part two, a connecting table two and a cylinder; the connecting table one is provided with the moving driving part two; the driving end of the moving driving part two is provided with the connecting table two; three cylinders are arranged on the connecting table two; three groups of concrete seamless floor strength data are collected by the three dynamic rebound apparatuses for parallel comparison, so that the error is reduced, and the test area of the dynamic rebound apparatus is protected by the cylinder.

The invention relates to the technical field of automatic acquisition, in particular to an automatic riverbed material acquisition control system and method based on Beidou navigation. The method comprises the following steps: acquiring a Beidou satellite multi-dimensional data set; performing original data preprocessing on the Beidou satellite multi-dimensional data set to obtain a Beidou multi-dimensional standard data set; performing multi-source data fusion based on the Beidou multi-dimensional standard data set to obtain riverbed multi-source fusion data; generating a riverbed sampling decision by using the riverbed multi-source fusion data; therefore, through comprehensive application of multi-source data fusion, path optimization and automatic data evaluation, the problems of incomplete data, unreasonable sampling path and low report generation efficiency in the traditional riverbed data sampling process are solved, and the riverbed data acquisition precision, efficiency and intelligent level are improved.

The invention specifically relates to the technical field of digital twinning, and discloses a seamless steel tube size parameter detection and deviation correction system based on digital twinning, which comprises a multi-dimensional data acquisition module, a digital twinning model construction module, a deviation quantitative evaluation module, a correction scheme generation module, a correction scheme iteration module and a knowledge model optimization module, a real-time transmission mechanism of data acquisition-deviation analysis-correction decision is constructed, full-dimensional parameters of the seamless steel pipe are acquired in real time through a multi-dimensional data acquisition module, a digital model of the steel pipe is synchronously input, and a quantitative model driven by full-process data is constructed, so that the full-dimensional parameters of the seamless steel pipe are obtained. The size deviation degree and the surface quality score are accurately calculated through a deviation quantitative evaluation model, comprehensive deviation grades are divided, an initial correction scheme is generated based on deviation types and grades, parameters are quantified and adjusted through an iterative optimization correction scheme, an iterative correction-case precipitation-model optimization closed-loop structure is constructed, continuous evolution of the system is achieved, and the system quality is improved. The production efficiency is improved.

The invention relates to the technical field of neodymium iron boron detection, in particular to a hardness detection device and method for sintered neodymium iron boron, and the device comprises a bottom plate and the like; the bottom plate is a bearing carrier of the detection device, a plurality of air cylinders are fixedly mounted on the bottom plate, and the mounting frame is a square frame and is fixedly mounted on telescopic rods of the air cylinders; the guide seat is fixedly arranged on the top surface of the bottom plate, a sliding groove is formed in the middle of the guide seat, a threaded seat is fixedly arranged at one end of the guide seat, and a fixing block is fixedly arranged at the other end of the guide seat; the supporting plate is installed in the sliding groove of the guide base in a sliding mode. Through the adjustable clamping piece and the replaceable extrusion contact, the device can adapt to sintered neodymium iron boron blanks with different shapes and hardness, the application range of the device is expanded, then the hardness detection mechanisms at multiple positions are used for synchronously carrying out multi-point-position hardness detection on the neodymium iron boron blanks, and the comprehensiveness and high efficiency of neodymium iron boron blank detection are achieved.

The hardness detection equipment comprises an operation table, foot pads are fixedly connected to the bottom of the operation table, a protection cover is fixedly connected to the top of the operation table, a vertical frame is fixedly connected to the top of the operation table, the vertical frame is fixedly connected with a hardness detector, and the operation table is provided with a supporting mechanism. The hardness detector has the beneficial effects that the hardness detector is provided with the detection extrusion head, the camera, the displacement sensor and the pressure sensor, the detection extrusion head extrudes a PVC pipe, indentations can be generated, the camera shoots indentation image data, the pressure sensor senses a pressure value at the same time and feeds the pressure value back to the controller, and the detection extrusion head detects the hardness of the PVC pipe. The controller analyzes the hardness of the PVC pipe according to the indentation depth and the pressure value, and an elastic supporting block of the supporting mechanism has a supporting effect on the inner wall of the PVC pipe in the hardness detection process of the PVC pipe, so that the PVC pipe is prevented from being crushed in the extrusion process, and the hardness test effect is not influenced; the adjusting handle rotates to drive the threaded rod to rotate, the heights of the extension rod and the elastic supporting block are adjusted, and the device is suitable for PVC pipes with different diameters.

The invention relates to the technical field of material science, and particularly discloses a glaze performance evaluation method and system based on multiple application scenarios, and the method comprises the steps: obtaining the original data of the hardness value and wear loss of glaze, carrying out the standardization processing, calculating the hardness distribution index and wear resistance index, and carrying out the comprehensive analysis and classification of the glaze, thereby achieving the evaluation of the performance of the glaze. Qualified glaze and unqualified glaze are distinguished; then carrying out high-temperature stability test on the qualified glaze, and screening out the glaze with high thermal stability; and finally, a particle swarm optimization algorithm is adopted to search for an optimal solution of a hardness value and a wear loss regulation interval, and it is ensured that the glaze shows excellent performance in a changeable application environment. Through the systematic evaluation process, the problems of fuzzy standard, lack of scientific basis, poor performance consistency and low evaluation efficiency in a traditional evaluation method are solved, the consistency and reliability of glaze performance are effectively improved, the product quality is ensured, and the evaluation efficiency is remarkably improved.