1307results about "Investigating material hardness" patented technology

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 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 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 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 discloses a coastal corrosion geological environment structure corrosion resistance evaluation method and system, and relates to the technical field of building structure corrosion resistance evaluation. The method comprises the steps of data acquisition, coast environment corrosion factor data is acquired by arranging a sensor module, related data of a building structure is acquired at the same time, and the accuracy of assessment data and assessment results is effectively improved by considering multiple factors into the corrosion resistance assessment of the building structure in the coast region; meanwhile, a coupling corrosion rate correction model is constructed, corrosion factor data monitored in real time and real-time data of the building structure are combined, the purpose of evaluating the corrosion resistance of the building structure in the coastal area according to real-time changes of corrosion factors in the tidal period is achieved, the real-time performance of an evaluation result is guaranteed, and the evaluation efficiency is improved. And the accuracy of the evaluation data is further improved.

The invention relates to the technical field of metal fatigue life prediction, in particular to an additive manufacturing metal multi-axis high-cycle fatigue life prediction method based on defect characteristics. The method comprises the following steps: performing defect detection on a metal sample to obtain size parameters and position parameters of defects in the metal sample; determining the type of the defect in the metal sample and setting a first correction factor and a second correction factor; calculating the equivalent stress strength factor amplitude of the metal sample under multi-axial loading; acquiring a long crack propagation threshold value of the metal sample; normalizing the position parameters to obtain normalized position parameters; and establishing a fatigue life prediction model of the metal sample according to the normalized position parameters, the equivalent stress strength factor amplitude of the metal sample under multi-axial loading and the long crack propagation threshold value of the metal sample, and calculating the multi-axial high-cycle fatigue life of the metal sample. According to the method, the fatigue life of the metal material containing the additive manufacturing defects under multi-axis high-cycle fatigue loading can be accurately predicted.

The invention discloses a system and a method for rapidly screening illegal additives of health care products based on multispectral imaging, relates to the technical field of health care product detection, and aims to solve the problem of low detection accuracy caused by the fact that an embedding structure hinders spectral signal penetration in the prior art. The system comprises an embedding material characteristic analysis module, a targeted crushing parameter calculation module, a microcapsule crushing execution module, a multispectral imaging module and an illegal additive identification module, the embedding material characteristic analysis module is used for acquiring characteristic parameters of an embedding material in the microcapsule embedding type health care product, and the characteristic parameters comprise hardness, thickness, elastic modulus, thermal decomposition temperature, Poisson's ratio and thermal expansion coefficient of the embedding material; and the targeted fragmentation parameter calculation module is used for receiving the characteristic parameters and calculating the characteristic parameters through a multi-dimensional algorithm to obtain targeted fragmentation parameters. The method has the advantage that illegal additives in health care products can be quickly and accurately screened.

The invention discloses a concrete material strength detection and analysis system, and relates to the technical field of constructional engineering quality detection. The system comprises a data acquisition module, a data preprocessing module, a fusion and analysis module, a fusion and analysis module and a visual report generation module. Wherein the data acquisition module is used for acquiring multi-source original data of concrete strength; the data preprocessing module is used for performing cleaning, format standardization and invalid value elimination operation on the multi-source original data and storing the multi-source original data in the central database; the fusion and analysis module is used for carrying out strength prediction in future time by adopting a dual-mode comparison prediction method, and sending warning information to detection personnel when a strength prediction value exceeds a prediction threshold value; and the visual report generation module is used for automatically generating a detection report and an analysis chart conforming to a standard format. According to the method, the analysis and evaluation of the concrete strength can be realized by fusing the multi-source detection data and the process data and utilizing a machine learning algorithm.

The invention provides a lunar lava tube rock wall mechanical parameter testing device and method based on a rebound principle, and relates to the technical field of lunar rock-soil mechanics detection.The device comprises an ejection module, a driving module, an energy storage locking module, a control module and an impact measuring module which are arranged in a protective shell; the ejection module comprises an ejection body of a hollow cylinder structure, the ejection body is arranged in the center of the interior of the protective shell, the upper end face of the ejection body is connected with a clamping pin, a pair of lug stoppers are arranged on the outer walls of the lower portions of the two sides of the ejection body, and the lug stoppers are reset through first springs. The lower end face of the elastic striking body is connected with the upper end of the extension spring, the lower end of the extension spring is connected with the upper end of the striking end support, and the lower end face of the striking end support is connected with the upper end face of the striking rod. The problems that a traditional Schmidt hammer is poor in adaptability in the lunar environment, low in automation degree, ineffective in parameter measurement basis and the like are solved.

The invention relates to the technical field of rock mechanics and deep stratum reconstruction engineering, and discloses a method for determining a roof rock stratum fracturing horizon based on multi-scale rock mechanics characterization, and the method comprises the following steps: firstly, obtaining drilling cuttings to prepare a nanoindentation test piece, and carrying out gridding dotting test and mineral scanning; secondly, calculating micromechanical parameters such as reduction modulus, fracture toughness, elastic index and plastic work ratio based on test data; constructing a macroscopic mechanical model by utilizing the microscopic parameters and the mineral distribution characteristics to carry out numerical simulation to obtain a macroscopic elastic modulus and uniaxial compressive strength; and finally, performing normalization and weighting processing on macro and micro parameters, constructing a comprehensive compressibility index and a comprehensive brittleness index, and optimizing a target fracturing layer position and a perforation position according to the comprehensive compressibility index and the comprehensive brittleness index. According to the method, cross-scale coupling of microscopic component attributes and macromechanical response is achieved, the problem of parameter acquisition caused by heterogeneity of deep rock strata is solved, the limitation of single-scale evaluation is overcome, and the fracture horizon identification precision and the engineering success rate are improved.

The invention discloses a shelf life kiwi fruit comprehensive quality quantitative evaluation method based on hyperspectral imaging and a convolutional neural network, and the method comprises the steps: 1, obtaining spectral images of kiwi fruits of different shelf lives through a hyperspectral imaging system, and extracting the original spectral data of a region-of-interest sample; step 2, measuring the soluble solid content, hardness and color parameters of the sample, normalizing the parameters with correlation, extracting a dominant factor combination with an accumulative contribution rate greater than or equal to 80% by using a factor analysis method, and constructing a KCQI (Kiwi berry Comprehensive Quality Index) based on factor load weight; step 3, preferably selecting a characteristic wave band related to the KCQI, and performing sample set division; 4, taking the spectral data of the characteristic wave band as input, and adopting a one-dimensional convolutional neural network to construct a quantitative prediction model of KCQI; and step 5, applying the model to a spectral image of a sample, generating a KCQI spatial distribution visual image pixel by pixel, and visually displaying the comprehensive quality change.

The invention provides a material hardness identification method and system based on electronic skin. The method is applied to the technical field of robot tactile perception. The method comprises the following steps: acquiring pressure array data and environmental data acquired when the electronic skin is in contact with a target material; carrying out space, time, frequency domain and gradient multi-modal feature extraction on the pressure array data, and carrying out feature fusion to obtain a multi-modal feature vector; predicting the multi-modal feature vector by using a preset regression model to obtain a hardness predicted value; and classifying the hardness predicted values according to the environmental data to obtain the hardness category of the target material. According to the invention, high-precision soft and hard material identification is realized.

The invention relates to a mechanical property simulation method for researching the service life of an aluminum alloy material for a reactor. The simulation method for the life period mechanical property of the aluminum alloy material comprises the following steps: S1, preparing initial, middle and last stage aluminum alloy samples according to a < 27 > Al-< 28 > Si transmutation path of the aluminum alloy material; s2, representing the sample by using a transmission electron microscope, obtaining precipitated particle parameters, calculating a volume fraction f, fitting f and operation time t, and constructing a precipitation evolution model f (t); s3, performing high-energy ion irradiation on the sample, and performing nanoindentation experiment and load-depth curve fitting to obtain nano hardness H; s4, based on the f (t), establishing a relation model of the nano hardness H and the irradiation damage D; and S5, calculating the change quantity of the nano hardness H, converting the change quantity into the change quantity of the yield strength, associating the irradiation damage D with the service time T, and establishing a life period yield strength prediction model. According to the method, the mechanical property of the aluminum alloy in the full service cycle of the research reactor can be accurately evaluated.

The invention provides a comprehensive optimization method for blasting control in a complex geological environment, and the method comprises the steps: collecting rock mass characteristic data, including hardness and density distribution, in the complex geological environment through a field sensor, integrating multi-source information through a data fusion method, and obtaining a unified rock mass characteristic model; the soft rock disturbance degree is evaluated through slope stability influence indexes, a blasting time sequence is calculated through a particle swarm optimization algorithm, a delay interval is prolonged for a high disturbance area, and an accurate blasting time sequence scheme is determined; generating pre-fracture formation path prediction according to the accurate blasting time sequence scheme, and if the adaptation degree of the prediction path and the target geology is lower than a threshold value, iterating time sequence parameters to obtain a regular pre-fracture formation model; and deriving energy release distribution from the regular pre-crack formation model, integrating a time sequence scheme and a charging structure, and simulating the overall blasting efficiency to obtain final geological adaptive blasting control parameters.

The invention relates to the technical field of aluminum alloy detection, and discloses clamping equipment for aluminum alloy detection, which comprises a base, two electric guide rails are symmetrically mounted on the base, an area for placing an aluminum alloy profile is formed between the two electric guide rails, brackets are mounted on the two electric guide rails, a bearing seat is mounted on each bracket, and elastic rolling pieces for pressing the aluminum alloy profile are mounted on the bearing seats; the electric guide rail can drive the support to drive the elastic rolling piece on the bearing base to roll on the surface of the aluminum alloy profile. And a hardness detection piece is mounted in the elastic rolling piece. Rapid identification of surface unevenness is achieved through the elastic rolling part and the displacement sensor, local hardness can be quantitatively detected through the built-in hardness detection part, internal defects caused by insufficient hardness are prevented, dynamic pressing and friction resistance detection of the profile in the full-length range are achieved in cooperation with the adjustable limiting detection part and the pressure sensor, and the detection precision is improved. The comprehensiveness of pre-screening before flaw detection is improved, and the condition of missing detection is effectively prevented.

The invention is applicable to the technical field of rock detection, and provides rock hardness detection equipment for geological exploration, which comprises a protective shell, support arms and hardness detection modules, the support arms are symmetrically and fixedly connected to two sides of the top of the protective shell, the hardness detection modules are mounted at the tops of the support arms, and the rock hardness detection equipment further comprises: an auxiliary support assembly arranged in the protective shell, the auxiliary supporting assembly comprises a first sliding frame slidably connected into the protective shell, a first spring is fixedly connected between the first sliding frame and the outer wall of the protective shell, a plurality of first round rods are evenly and fixedly connected to the surface of the first sliding frame, and a plurality of positioning rings are evenly and fixedly connected to the outer walls of the first round rods. The embodiment of the invention has the beneficial effects that the supporting rod is adjusted in a sliding manner according to the shape of the bottom of the rock, so that the top of the rock can be kept in a horizontal state when the hardness of the rock is detected after the supporting rod is limited, thereby ensuring that the detection equipment does not slip due to inclination of the top of the rock in the detection process; and the rock hardness detection precision is improved.

The utility model discloses a constructional engineering quality detection device, and belongs to the technical field of concrete detection. Comprising a rebound apparatus and further comprises a main frame, a sliding seat, a surrounding plate, a clamping sleeve and a top pressing plate, the main frame is of a C-shaped structure, and a laminated board is integrally manufactured at the bottom of the main frame; slideways are formed in the two sides of the main frame; the sliding seat comprises a sliding plate arranged on the inner side of the main frame, a sliding block is integrally formed on the sliding plate, and the sliding block is arranged on the inner side of the sliding way in a sliding mode; the coaming is mounted outside the main frame in a sliding manner, and the coaming is rotationally connected and fixed with the sliding block; a first grip is fixed to the side, away from the opening of the main frame, of the coaming. Penetrating holes are oppositely formed in the upper parts and the lower parts of the coaming and the sliding seat; a position adjusting screw rod is fixed at the outer part of the surrounding plate; the constructional engineering quality detection device disclosed by the utility model can assist a rebound apparatus to vertically apply pressure to a sampling surface, ensure that a detection result is effective, and can improve the detection convenience.

The utility model relates to a double-objective-lens three-pressure-head visual brinell hardness tester which comprises a shell, a turntable housing is arranged at the inner top of the shell, and a rotatable five-functional-position turret mechanism is arranged in the turntable housing. According to the utility model, by adopting the five-functional position turret mechanism, the rapid switching of the objective lens and the pressure head is realized, so that the test efficiency is greatly improved, meanwhile, the design of the double objective lenses enables the hardness tester to observe indentations under different magnification times, the measurement accuracy and flexibility are improved, and the test efficiency is improved. The design of the three detection pressure heads enables the durometer to easily adapt to different test requirements without replacement, the arrangement of the camera mechanism enables the test process to be recorded in real time and facilitates subsequent data analysis and processing, the host is used as the core of the control system and can realize automatic control of the whole test process, and the display is embedded in the face frame, so that the whole test process is more convenient. Therefore, the user can visually see real-time data in the testing process, and the operation is more convenient.

The invention relates to a method for evaluating mechanical failure of a positive pole piece of a polycrystalline structure in a lithium ion battery, which belongs to the technical field of lithium ion batteries, and can be used for respectively evaluating the intrinsic performance of crystal grains, the stress concentration degree of a crystal boundary and the integrity of the crystal boundary of secondary particles through nanoindentation tests of different indentation areas. A multi-dimensional evaluation means is provided; according to the method, the mechanical failure degree is evaluated through quantitative mechanical property indexes, a scientific basis is provided for optimal design of the lithium ion battery positive electrode material, and the cycle life and the safety performance of the lithium ion battery can be improved. The method is used for evaluating the particle integrity and the grain boundary damage degree of the layered oxide polycrystalline positive electrode of the lithium ion battery, the technical problem that mechanical failure evaluation of the polycrystalline positive electrode of the lithium ion battery is difficult is solved, and the technical effect of accurately evaluating the grain integrity and the grain boundary cracking process after circulation is achieved.

The utility model provides an engineering material hardness detection device which comprises a detection table, supporting columns are installed on the two sides of the top of the detection table, a cross beam is installed at the top ends of the supporting columns, a through installation groove is formed in the surface of the cross beam, and a detection assembly used for detecting materials is installed in the installation groove. Electric push rods are installed on the outer side faces of the two supporting columns, the telescopic ends of the electric push rods extend to the inner sides of the supporting columns and are connected with clamping assemblies, and the to-be-detected materials can be clamped and fixed in a wrapping mode through the arranged clamping assemblies, so that the clamping device can adapt to clamping and fixing of the materials of different shapes, corresponding clamps do not need to be replaced, and the clamping efficiency is improved. The detection efficiency is effectively improved, the hardness of the material can be detected through the arranged detection assembly, and when the moving block transversely moves along the lead screw, the blowing nozzle blows away impurities on the surface of the material, so that the impurities on the surface of the material are prevented from influencing the detection precision.

The invention relates to the technical field of building materials, and discloses a method for determining the thickness of a concrete interface transition area based on nano scratches, which comprises the following steps: pretreating a to-be-detected sample; the method comprises the following steps: testing a to-be-tested sample through scanning based on a nano scratch tester to obtain a scratch depth-scratch distance mean value curve; based on the scratch depth-scratch distance mean value curve, boundary points between the base body and the interface transition area and boundary points between the interface transition area and aggregate are extracted, and the thickness of the interface transition area is calculated; calculating a fracture toughness mean value based on the scratch depth characterization value and the transverse scratch load, and drawing a fracture toughness-scratch distance mean value curve; and putting the boundary points into the fracture toughness-scratch distance mean value curve, and verifying the calculated thickness of the interface transition area. According to the invention, continuous and accurate measurement of the ITZ thickness is realized based on the difference between mechanical properties of different phases, and a scientific tool is provided for dynamic evaluation of concrete durability.

The invention provides a crack pouring glue compression rebound recovery rate test system and method, and relates to the technical field of rebound recovery rate test.The crack pouring glue compression rebound recovery rate test system comprises a tester, a high-precision injection ball and a large sample containing vessel; the tester comprises a machine body, a touch control type control display screen is mounted on an inclined panel of the machine body, a group of function buttons are mounted on the inclined panel of the machine body, the machine body is provided with a stepped circular groove, and the large sample containing vessel is matched with an upper side circular groove of the stepped circular groove; the machine body is connected with a U-shaped frame, and the U-shaped frame is connected with a first laser distance measuring sensor. Aiming at the defects in the prior art, the invention develops the system and the method for testing the compression resilience recovery rate of the crack pouring glue, and the high-precision penetration ball is adopted, so that the contact area with a sample is increased, and the detection error is reduced. By optimizing a hardware structure (replacing a high-precision sensing assembly) and control logic, automation and high precision of a test process are realized.

The invention relates to the field of material testing, and discloses an indentation testing device which comprises a supporting unit, a testing unit and a driving unit, an electric cylinder of the driving unit can drive a pre-contact assembly and an indentation assembly to reciprocate, so that rapid movement in a large range is realized, and a contact ball and a pressure head can rapidly approach a tested piece; the contact driver can drive the contact ball to reciprocate, so that the contact ball is in contact with the tested piece, and the contact ball is connected with an elastic body made of a memory alloy material; when the pressing head is pressed in, the piezoelectric stack of the driving unit is used for driving the pressing rod and the pressing head to move through the piezoelectric amplification mechanism, and the pressing-in precision of the pressing head is improved. According to the invention, the electric cylinder is used for macroscopic driving, and the piezoelectric stack is combined to precisely control the pressure head, so that the test precision and the test efficiency are improved, and a proper mechanical model is established after a press-in load-depth curve is obtained. The invention further provides an indentation testing method.

The invention belongs to the technical field of water pump blade detection, and particularly provides a blade hardness detection device for water pump production, which comprises a base, an operation turntable is rotatably arranged at the upper part of the base, and an integrated type integrated detection assembly and a negative pressure adsorption type positioning assembly are circumferentially and uniformly distributed on the operation turntable; the integrated type integrated detection assembly is arranged above the negative pressure adsorption type positioning assembly, and the integrated type integrated detection assembly and the negative pressure adsorption type positioning assembly are correspondingly arranged; a pre-acting principle is combined with a negative pressure adsorption effect, after a water pump impeller is integrally positioned, hardness detection is carried out on multiple groups of blades at the same time, and in the whole detection process, a main power motor is driven to intermittently work through signals of a gravity sensor; the integrated detection assembly and the negative pressure adsorption type positioning assembly synchronously operate in a feeding area, a detection area, a removal area and a discharging area respectively, automation and continuity of the detection process are achieved, and the detection efficiency is improved.

The invention discloses powder metallurgy gear performance detection equipment, and relates to the technical field of powder metallurgy gear performance detection. The powder metallurgy gear performance detection equipment comprises a detection table, a machine body fixedly connected to the detection table and a detection head installed on the machine body, a plurality of clamping mechanisms which are located in containing grooves and used for containing gears are installed in the circumferential direction of an inner cavity of a rotary drum at equal intervals, and an ejection mechanism is installed on the detection table. According to the gear clamping device, the clamping mechanism is matched with the pushing and jacking mechanism, intermittent rotation of the rotary drum is combined, stable clamping of a gear between different detection angles can be kept all the time, clamping and loosening can be automatically completed, and the gear clamping device is simple in structure, convenient to use and high in practicability. Manual repeated clamping and repositioning are not needed, tiny offset and measurement errors caused by multiple operations are reduced, labor intensity and time consumption are reduced, and positioning precision and measurement consistency of continuous detection of batch gears are improved.

The invention provides a method for measuring the dynamic hardness of a material based on bullet impact indentation. The method comprises the following steps: carrying out decontamination and polishing treatment on the surface of a target material; measuring the elastic modulus of the to-be-measured area; the hard spherical projectile is launched to impact the to-be-measured area to form an impact pit, and the springback speed of the projectile is measured in situ; measuring geometric parameters of the impact pit; establishing a contact force model of the elastic unloading section impacted by the projectile; and with the springback speed and the geometric parameters of the pit as input, obtaining the maximum loading force through a contact force model, and finally calculating the dynamic hardness. The dynamic Myer hardness is calculated by measuring the bullet rebound speed and pit parameters through the bullet impact indentation test without depending on real-time data acquisition of a high-frequency force / displacement sensor, so that the problem of strain rate upper limit caused by hardware limitation in the traditional technology is solved, and the blank of dynamic Myer hardness measurement under the high strain rate is filled up.

The invention discloses a coke residue characteristic detection method and system based on a visual tactile sensor, and the method comprises the steps: carrying out the contact scanning of a coke residue sample through the visual tactile sensor, and obtaining the surface three-dimensional topological point cloud data and distribution force vector data of the coke residue sample; carrying out regional or multi-angle scanning on the coke residue sample, and fusing and reconstructing surface three-dimensional topological point cloud data obtained by each scanning into a complete three-dimensional surface model; extracting a plurality of predefined feature parameters from the three-dimensional surface model and the distribution force data, and performing normalization processing to form a structured feature vector; and based on the structured feature vector, coke residue characteristic detection is carried out through a predefined discrimination rule or a machine learning model. According to the method, the visual tactile sensor is used for performing three-dimensional reconstruction and distribution force acquisition on the characteristics of the coke residue, the apparent description of manual visual inspection is converted into quantifiable three-dimensional shape parameters and characteristic indexes, and the problems that manual judgment is high in subjectivity and cannot be quantized and traced are solved.

The invention discloses a piezoelectric driving micro-nano scratching instrument, and belongs to the technical field of material mechanical property detection. The scratch tester comprises a piezoelectric driving system, a multi-mode detection system and a control and data processing system. The core is that the piezoelectric driving system is completely driven by piezoelectric elements, and a displacement table adopts a clamping type stepping mechanism based on a flexible hinge, so that the combination of nanoscale motion precision and large stroke is realized; the multi-mode detection system innovatively integrates an electrical impedance detection loop composed of a conductive pressure head and a sample, can sensitively capture microscopic damage and failure behaviors of a material in the scratching process, and carries out synchronous fusion analysis with signals of a force sensor and a displacement sensor. According to the invention, the defects of insufficient precision and single detection means of the traditional scratch tester are overcome, and the accuracy and reliability of detecting the interface bonding strength and other mechanical properties of materials such as films and coatings are remarkably improved.

The invention relates to the field of materials and processes for automobile parts, in particular to a homogenization evaluation method for hardenability of Ti-containing carburizing steel and application. According to different specifications and different looseness and segregation levels of the round steel, sampling regulation is carried out on the center part and the center part of the section of the Ti-containing carburizing steel round steel, and the hardenability and the hardenability bandwidth of the carburizing steel can be more truly reflected. When the hardness of the tail end hardenability sample is detected, two surfaces equidistant from the circle center of the section of the round steel are detected, a telecentric surface far away from the circle center of the section of the round steel and a proximal surface close to the circle center of the section of the round steel are detected, and compared with the current national standard, the detection result is more scientific and accurate. The method can be applied to almost all carburized steel bars with large component fluctuation, the uniformity is truly reflected, technicians can select raw materials with proper hardenability bandwidth to be applied to shaft gear parts with different size characteristics and using performance requirements, and the application prospect is very wide.

The invention relates to a method for obtaining mechanical properties of granite and application of the granite in deep geological disposition, local mechanical parameters (elastic modulus, hardness and fracture toughness) of the granite are obtained through a nanoindentation experiment, the reliability of a model is verified in combination with finite element numerical simulation, and experiment and simulation results show that the mechanical properties of the granite can be obtained. The method can accurately predict the mechanical property degradation trend of the granite in the high-temperature and high-pressure environment (for example, the elastic modulus is reduced to 54.71 GPa at 650 DEG C, and the hardness is reduced by 34.38%), and an efficient and reliable analysis tool is provided for surrounding rock stability evaluation of a high-level radioactive waste geological repository.