594results about How to "High degree of fit" patented technology

The invention provides a fracture-vug type oil reservoir water-flooding development effect evaluation method. The fracture-vug type oil reservoir water-flooding development effect evaluation method comprises the steps that fracture-vug units to be evaluated are divided into a plurality of injection and production well sets; the well control coefficient of each injection and production well set is calculated, and the well control effect interval of each well set is determined combined with a corresponding preset well control coefficient index; the water-flooding recovery efficiency and the oil exchange rate of per ton water of each injection and production well set are calculated, and the development effect interval of each well set is determined combined with a corresponding preset development coefficient index; the cumulative water content and the water storage rate of each injection and production well set are calculated, the judging that whether water channeling exists or not is performed according to the cumulative water content, a water storage effect interval is determined combined with a preset water storage rate index; the non-dimensional flexible yield ratio, the single reservoir pressure drop and the artificial water-flooding index of each injection and production well set are calculated, the natural energy interval of each well set is determined combined with a corresponding preset natural energy index, a water-flooding effect interval is determined combined with a preset artificial water-flooding index. The fracture-cavern type oil reservoir water-flooding development effect evaluation method fully reflects the water injection effect of the injection and production well sets and the reason of achieving the effects, and therefore the foundation and the basis and the pertinence of the provided adjustment measure are better achieved.

The invention discloses a bionic gradient knee femoral prosthesis structure and a production method thereof. The prosthesis structure comprises a smooth curved-surface shell, a post-osteotomy completely-covering joint face, a gradient porous structure and a fixing device. The curved-surface shell is based on the shape of the distal end of a connate femur. The post-osteotomy completely-covering joint face reversely spreads to the distal-end curved surface of the connate femur. A solid more than 5mm distant from the curved surface is replaced by the gradient porous structure, and the fixing device is formed on the distal-end plane on the inner side of a femoral prosthesis. Compared with conventional standard prostheses, the prosthesis structure has the advantages that matching degree is high, and the prosthesis highly fits the bone shape of a connate knee and is adaptable to motions of a patient. The bionic gradient knee femoral prosthesis structure is easy to produce, and conventional production methods for conventional bionic gradient prostheses are complex; by the 3D (three-dimensional)-printing production method, prostheses can be customized according to individual differences of patients, production period is short, cost is low, and a possibility for application and development of individualized therapy is provided.

The invention discloses a test method and a test device for simulating stratum deformation caused by pipe jacking construction. The test method comprises the following steps: (1) installing a lateral flexible loading bag; (2) filling with earth; (3) installing a simulated jacking pipe; (4) installing a loading system; (5) loading; (6) monitoring an initial value; (7) simulating an excavated stratum loss process; and (8) organizing and analyzing test data. The lateral flexible loading bag is adhered to the inner wall of a model box, the left end of the model box is connected with the lateral flexible loading bag, the right end of the model box is connected with a lateral loading pressure gauge, and the lateral loading pressure gauge is connected with a lateral loading booster pump through a lateral pressurizing water injection pipe; an exhaust valve is arranged at the top of the lateral flexible loading bag; a circular hole is formed from the front side wall of the model box to the bottom of the model box; studs are welded at the periphery of a circular jacking pipe preformed hole; the right end of the simulated jacking pipe is placed in the circular jacking pipe preformed hole in the front side wall of the model box, and the left end of the simulated jacking pipe is placed close to the rear wall of the model box. The test device disclosed by the invention is reasonable in structure and convenient to operate and is used for simulating a model test of stratum deformation caused by pipe jacking tunnel construction.

The invention relates to an asphalt mixture life prediction method considering a fatigue-creep interaction damage effect, and belongs to the field of road engineering. The method comprises the following steps: (1) determining a complex modulus of an asphalt mixture under the action of a period load; (2) determining a damage variable of the asphalt mixture; (3) building a creep damage equation and a fatigue damage equation of the asphalt mixture respectively; (4) building an asphalt mixture life prediction model under the combined action of creep damage and fatigue damage. Compared with a conventional asphalt mixture life prediction method, the viscoelastic behavior of the asphalt mixture is considered and a more accurate prediction model is built. The method accurately describes asphalt mixture damage failure process and rule, has the advantages of wide application range and reliable calculation results, and provides a more reliable method for structural design of an asphalt pavement.

The invention discloses a traffic flow prediction method of a divergence convolution recurrent neural network based on a space-time diagram. The traffic flow prediction method is characterized in thata directed weighted graph of a road network is constructed based on spatial features of a traffic network, then a traffic flow prediction model of a graphic divergence convolution recurrent neural network is constructed by taking the directed weighted graph as a basic unit of prediction, deep learning is carried out by means of time-space characteristics of the traffic network, time-space prediction is carried out on the traffic flow of the traffic road network, a final traffic flow prediction model is constructed, and real-time prediction of the traffic flow is realized. The traffic flow prediction method has the advantages of precise prediction and high fitting degree.

The invention provides a double safety and effectiveness inspection method of human lumbar bone and implant, and belongs to the field of medicine. The method comprises the following steps: acquiring a 3D (three-dimensional) rendering model of lumbar body bone, lumbar disc and interspinous ligament by a 3D reconstruction technology; performing 3D grid division to the 3D rendering model, and giving attributes of a heterogeneous material to the 3D rendering model; performing 3D modeling to an implant; assembling the lumbar body bone, the lumbar disc, the interspinous ligament and the implant, and analyzing stress and strain of the assembly by adopting uniformly distributed nodal load through a finite element analysis method; simulating visible finite element analysis by a computer before the implant is implanted into a human body. Therefore, the verification requirement to bone and implant double safety and effectiveness can be fulfilled, the damage of the implant to original human lumbar bones can be prevented, double safety and effectiveness of the bones and implant can be guaranteed, the manufacture cost can be effectively reduced along with convenience and quickness, and individual and industrial manufacturing of a human lumbar bone implant can be realized. The method is applicable in the field of implant stress-strain analysis in the orthopedics department.

This invention disclose a kind of high resolution nonlinear reservoir object inversion method, uses a kind of nonlinear reservoir lithologic object convolution module to build the function relation of wave impedance and porosity / argillaceous content; describes the physical relation of complex rock by analyzing multilevel structure and determining two-way edge wavelet; realizes the combination of the certainty inversion, statistic inversion and nonlinear theoretics; then realizes the high resolution reservoir object parameter inversion of composite geology, well logging and earthquake wave impedance information base on both inverse operator inversion and positive operator reconstructed algorithm, gets high resolution reservoir object cross section (such as porosity, argillaceous content).

The invention provides a personalized advertisement pushing system and method. The personalized advertisement pushing method comprises the steps of: grabbing a webpage browsed by a user in the internet and carrying out mirror image backup; performing image drawing on the user according to the webpage subjected to the mirror image backup, and obtaining identity information or / and life information of the user; according to the identity information or / and life information of the user, mining various potential consumption demands of the user; and pushing advertisements matched with the potential consumption demands to the user. According to the personalized advertisement pushing system and method, on the basis of collecting a large amount of browse data of the user, image drawing on the user is realized through data analysis, and a user image is applied to advertisement recommendation; and user preferences are presented in a three-dimensional manner, and then deep advertisement pushing with relatively high matching degree is carried out, so that the user experience is improved.

The invention relates to a municipal drainage pipe network diagnostic assessment method giving consideration to a key node. The method includes the following steps that (1) the key node of a municipal drainage pipe network is obtained, a water level monitor and a flow monitor are additionally arranged at the position of the key node, actual running water level and flow data of the key node are obtained, and on-site pipe data at the position of the key node are obtained through CCTV measurement; (2) in cooperation with the actual running water level and flow data, topological data of the drainage pipe network, the on-site pipe data, boundary water level data, GIS data, ground elevation data and other data of the key node, a municipal drainage pipe network hydraulic model giving consideration to the key node is built; and (3) calibration is carried out on the municipal drainage pipe network hydraulic model, the municipal drainage pipe network hydraulic model obtained after calibration is adopted for simulating the running state of an actual municipal drainage pipe network system, and the running state of the system is assessed. Compared with the prior art, the municipal drainage pipe network diagnostic assessment method has the beneficial effects of giving consideration to the key node, being accurate in modeling, capable of achieving combined assessment, real and effective, improving efficiency and the like.

The invention discloses an expansive-soil slope hygroscopic deformation model experiment method and a system. The expansive-soil slope hygroscopic deformation model experiment method comprises following steps: A, soil samples are turned and subjected to sun drying so as to control water content and soil filling thickness; B, soil filling is carried out by layers, slope cutting is carried out uniformly, and a part of monitoring components are buried; C, an obtained soil slope is allowed to stand until cracks are generated, and a displacement sensor is arranged; D, physical quantity initial values are recorded; E, a rainfall simulator is used for realizing dropping-pouring type concentrated rainfall, and rainfall amount is controlled; F, physical quantities and rainfall amount are monitored according to rainfall stages; G, a rainfall-evaporation cycle is carried out repeatedly so as to stimulate drying and watering cycle; and H, slope morphologic change is recorded, and results are analyzed. The system comprises a model case, monitoring components, and a rainfall simulator; the monitoring components are arranged in the model case; and the rainfall simulator is arranged on the upper part slope shoulder of the model case. The expansive-soil slope hygroscopic deformation model experiment method and the system are suitable for a plurality of expansive-soil slope hygroscopic deformation model experiments, and possess significant importance for researches on expansive-soil slope stability and catastrophe mechanisms.

The invention relates to a collision case playback system of the cars and two-wheeler in the computer application technical field, wherein an accident site reconstitution module collects the accident field data and picture, reconstitutes and reverts the site; a two-wheeler driver modularization dummy customizing module builds a dummy model matching with the body shape of the driver, extracts the damaged sensitive parts of the dummy model, sets up a finite element model, becomes a new conbination dummy model combined with the multi-rigid body dummy main body model; a collision process emulating module performs the scaling of model matching with the sufferer bodily form characteristics, meanwhile builds the integral accident site three-dimensional model before the accident, and simulates and computes the primary collision result; an optimization recurrence module builds the optimization flow, optimizes the collision simulation; an accident recurrence result post-processing module displays the optimized simulation result in the collision process animation and the collision parameters. The invention can realizes the site information collection, fast simulation and modelization, short treating period, high precision and high reliability.

The invention discloses a server load prediction method and system based on a Markov chain and a time sequence model. The method comprises the following steps: step 1, periodically sampling and updating load information of a server by utilizing a sliding window method, and generating a load value time sequence; Step 2, establishing an ARIMA model according to the load value time sequence, and correcting the predicted load error of the ARIMA model by using a Markov chain to obtain a corrected load predicted value; And step 3, each host reports the corrected load prediction value to the dispatcher of the server cluster where the host is located, and a decision basis is provided for the dispatcher to perform task distribution. The server load prediction method based on the Markov chain and the time sequence model can provide a decision basis for subsequently realizing reasonable scheduling of computing resources.

The invention provides an elevator running detection method and device based on relative air pressure and height error correction. The real-time elevator car height is calculated according to the relative air pressure of the real-time elevator position and the previous elevator leveling position, and the elevator leveling state is judged by calculating changes of air pressure data within the preset time; whether the leveling fault exists in an elevator car or not is judged through the comparison of the real-time height and the standard height; the standard height serves as the standard value,and accordingly the error existing during real-time elevator car height calculation and judgment is corrected; the current floor number is calculated through comparison of the real-time height and thestandard height; the elevator car running direction is judged according to the front-back relative air pressure difference of different positions during elevator car running; and elevator car runningspeed is calculated through the real-time height difference during elevator running within the sampling period and in combination with the sampling time. The device is low in economic cost and flexible in installing position. The coincidence degree between the elevator car running information obtained through analysis of a calculation method based on relative air pressure and height error correction and the actual elevator running information is high, and reliability is high.

The embodiment of the invention discloses a click stream data online analyzing method and a related device and system. The click stream data online analyzing method comprises the steps that click stream data are acquired from an advertisement server; key information is extracted from the click stream data; the click stream type corresponding to the key information is determined; a first time window is determined; according to the click stream type corresponding to the key information and the corresponding relationship between log time corresponding to the key information and the first time window, whether the key information needs to be filtered is determined; and if the fact that the key information does not need to be filtered is determined, the key information is used to generate the training data of an advertising forecast model. According to the technical scheme provided by the embodiment of the invention, the limitation of a processing resource on the acquired training data is reduced; the instantaneity of the advertising forecast model is improved; and the fitness of the advertising forecast model and online real-time data is improved.

The invention discloses a method for determining regional ionospheric layer delay. The method includes: collecting data; firstly establishing a regional ionospheric second-order term model according to the collected regional ionospheric VTEC (vertical total electron content) data; establishing a VTEC second-order term model and a fusion model of a neural network; adopting the fusion model to calculate VTEC values of puncture points of other positions in this area. By the method, computed results of the regional ionospheric layer delay are high in precision, and CORS (continuous operational reference system) measured results are wide in application range. A large number of engineering example application result analysis shows that precision of the computed results by the method is improved by 40% as compared to that by the VTEC second-order term model. Ionospheric layer space activity rules are high in fitting degree and high in timeliness, and convenience in use is brought. The ionospheric layer space activity rules can be obtained through analyzing according to fitting results of the neutral network, the ionospheric layer delay in any point in the area can be rapidly corrected, transmission precision and stability of radio waves can be improved, and technical support for better service for CORS can be provided.

The invention discloses a prediction and assessment method for stability of surrounding rocks of a mining roadway. The prediction and assessment method comprises the following steps: inputting measured data of influence factors of surrounding rocks of the mining roadway into a computer; then, retrieving sample data to set up a prediction model of a single kernel function support vector machine; combining selected global kernel functions with local kernel functions to form mixed kernel functions to set up a prediction model of a mixed kernel function support vector machine; utilizing a particle swarm algorithm to optimize penalty factors, kernel parameters and single kernel function coefficients of the predication model to set up a prediction model of a particle swarm algorithm-mixed kernel function support vector machine for stability of surrounding rocks of the mining roadway; and calculating prediction precision and reliability of to-be-predicted samples and assessing the maturity of the model. The prediction and assessment method for stability of surrounding rocks of the mining roadway is easily adopted and scientific. The grade prediction result of stability of surrounding rocks of the mining roadway and the maturity assessment result of the model are accurate and reliable and are highly consistent to the reality.

The invention provides a MOS transistor radio-frequency circuit simulation macro model and a parameter extraction method thereof. The simulation macro model comprises a MOS transistor simulation model, a gate resistor RG connected between a transistor gate node and a circuit grate node in series, a capacitor Cjun.s and a resistor Rjun.s and a capacitor Cjun.d and a resistor Rjun.d respectively indicating the a source electrode and a substrate, as well as the junction capacitance and parasitic resistance therebetween, and two resistor Rbulk and Rwell respectively indicating bulk resistance and trap resistance of the transistor. The four resistors Rjun.s, Rjun.d, Rbulk and Rwell are connected at one point, and indicate the parasitic resistance introduced by the substrate with a T-shaped structure. The invention also provides a method for extracting parameters of each element of a substrate network structure in the macro model using the equivalent circuit Y-parameter analytic method. The invention simulation macro model is suitable for frequency up to 20GHz, improves model accuracy of the MOS transistor in 20GHz high frequency domain, and expands the frequency application range of CMOS circuit EDA design.

The invention relates to a non-contact complex surface cone volume measurement system and method. The method includes the steps: firstly, providing three linear lasers to form a light sectioning plane and marking the contour of the section of a cone to be measured; secondly, providing a vertical lifter, moving the light sectioning plane relative to the cone to be measured; thirdly, providing a black and white camera for acquiring images and transmitting acquired image information to a computer for processing the image information to finally obtain the volume and a three-dimensional diagram of the cone to be measured. The measuring system and the method are simple and practicable, high in scanning speed and precision and low in requirement for the cone and environments and low in system cost.

The invention relates to a traffic flow prediction method based on stacked auto-encoder-support vector regression. A stacked auto-encoder-support vector regression combination model is built; input traffic flow data is normalized; feature learning is carried out; data features are obtained through unsupervised layer-by-layer feature training and supervised parameter fine adjustment; the obtained data features serve as new training and testing samples; prediction is carried out through a prediction layer; finally results are inversely normalized to obtain a prediction result. According to the method, the prediction effects superior to those of other existing prediction models are achieved in the aspects of the prediction precision, the convergence speed and the like; the feasibility is high; and the effect is good. The prediction method is good in prediction effect and high in fitting degree, can effectively solve the problem of the existing prediction model, prevents the generation oflocal optimization, greatly improves the prediction precision, is wide in applicability, is suitable for traffic flow prediction of not only bridges but also common road sections, and also has a relatively good effect in the aspect of short-time traffic flow prediction.

The invention relates to the field of power, in particular to a power transformer radiation audible noise calculating method. The method includes following steps: calculating sounding area and dimension characteristic parameters of a transformer; obtaining a r0 meter noise value Lp(r0) of a quasi emitting surface of the transformer, an average sound pressure level LPa and a sound power level Lw of noise of the transformer, and calculating noise distribution imbalance correction K of the transformer; and calculating to obtain an audible noise A sound level distant from the position r of the transformer. The power transformer radiation audible noise calculating method is simple and easy to implement, and characteristics such as the sounding area, dimension features and nonuniform noise distribution of the transformer are taken into full consideration, so that compared with calculating results obtained by other formulas, power transformer radiation noise values obtained by the method are more consistent with measuring results of transformers in 110-500kV transformer stations in China. The power transformer radiation audible noise calculating method is especially suitable for radiation audible noise calculation of large power transformers in power transmission and transformation projects, and also suitable for radiation audible noise calculation of noise sources capable of being stimulated to be cuboids.

The invention provides a seedling raising substrate for a machine-transplanted seedling tray for hybrid rice. The seedling raising substrate is prepared from the following raw materials in part by weight: 50 to 60 parts of crop stalk with lower than 10 percent of water content, 21 to 30 parts of animal waste with lower than 10 percent of water content, 13 to 20 parts of substrate carrier and 1 to 2 parts of substrate synergist, wherein the substrate synergist consists of the following components in percentage by mass: 65 to 75 percent of calcium cyanamide, 15 to 25 percent of calcium superphosphate, 7 to 9 percent of sodium silicate, 0.5 to 1.5 percent of boron and zinc and 0.5 to 1.5 percent of bioactive fungicide; the bioactive fungicide is one or several of bacillus subtilis, facultative anaerobe and agricultural photosynthetic bacteria; the raw materials are composted and fermented for three times to form the seedling raising substrate for the machine-transplanted seedling tray for hybrid rice. The seedling raising substrate is comprehensive in nutrition, is suitable for mechanized seedling raising for the hybrid rice, and ensures that germination and rooting of rice seeds are quick, the planting percent is high and seedlings are robust.

An optimizing control method for the biologic treating system of sewage features that starting from the technological parameters of the sewage treating system, the kinetic parameters of sewage, the minimal volume of reactor, the materials balancing principle, Monod equation and the circulating variables including BOD content, biomass concentration and returned amount are used to create a mathematical model for the sewage treating technology.

The invention discloses an automatic meat paste hammering machine, and relates to a machine automatically hammering massive raw meat into meat paste. The machine overcomes the defects that the fitness of square iron bars and an anvil face cannot be mastered well, the fineness, the elasticity and the like of the meat paste are not stable, the meat paste is easily deteriorated after hammering heating, and the physical energy is consumed when the massive raw meat is manually hammered into the meat paste with the two square iron bars in the current local characteristic technology of manual meat ball hammering. The machine is characterized in that a hammering area is formed by hammering a rotating anvil face arranged below in a fixed direction with a rectangular hammering bar in an extending hammering device of an air hammer; a used baffle device turns over the massive raw meat to the hammering area during rotation of the anvil face and avoids overflow; a coolant circulation cooling loop in the rectangular hammering bar reduces a heating state of the massive raw meat or the meat paste on the anvil face in a hammering process and improves the quality of a finished product until the massive raw meat is completely and uniformly hammered into the finished meat paste; and the characteristics of fine and elastic hammered meat paste and the like are shown better.

The invention discloses a CT image detection method based on deep learning. The method comprises the steps of preprocessing an original image to obtain a to-be-detected image; establishing a trainingneural network detection model to obtain a neural network CT image detection model; inputting the to-be-detected image into the neural network CT image detection model; Obtaining detection results, wherein the input to-be-detected image comprises cross section direction information. Different from an existing single-input and single-output model training mode, input is changed into five-dimensional data from a one-dimensional data image of a single slice, output is also changed into two-channel mask output from single output, model precision and focus fitting degree of a prediction result areimproved, precision reaches expert level, and clinical application can be carried out. Moreover, in the process, a neural network CT image detection model is established by using big data in advance,during judgment, a CT scanning image of a patient is directly input, the model is used for calculation, the model output response speed is high, and disease delay is not likely to be caused.

The invention discloses a rolling matching-based method for automatically identifying readings of water, electricity and gas meters. The method comprises the steps that a camera acquires real-time charging data pictures of the water, electricity and gas meters regularly and transmits the real-time charging data pictures to a singlechip system through a data line; the singlechip system carries out image binaryzation, charging digital block location, noise filtration, character segmentation and half-character judgment on the acquired charging data pictures to obtain segmented full-character and half-character pictures; a character spacing between upper and lower half-characters of an image to be identified; a template belt is connected according to the character spacing of the image to be identified; rolling and left-right moving of the template belt are combined for carrying out character matching; a character matching rate at a corresponding position is calculated; a maximum value is selected through matching the matching rates; and a template character corresponding to the maximum value is determined, an identification digital result is sequentially output from left to right according to the corresponding dial reading pictures and thus charging readings of the water, electricity and gas meters are obtained. The invention provides a method which is accurate in counting, is time and labor-saving, and is capable of obtaining the data of the water, electricity and gas meters duly.

The invention provides an airborne composite material profile accurate molding deformation compensation method. Aiming at the condition that the composite material molding method generally adopts a thermal molding method for manufacturing a die profile by using a profile the same as a composite material product data model, and the profile precision is reduced since the deformation rule of the profile for the single and large aircraft composite material cannot be obtained, the invention provides the airborne composite material profile accurate molding deformation compensation method. The method comprises the following steps: using the profile of the part data model as original data, manufacturing a test-piece and measuring according to data model geometric characteristic, establishing a test-piece deformation database, amending and compensating an original section curve to obtain an amended section curve, and acquiring an amended molding surface by using three-dimensional CATIA software, using the amended molding surface as a molding face for manufacturing the die, and then manufacturing a composite material product; therefore, the precision of the composite material product is greatly improved, the quality of the composite material profile is improved, and the production cost is reduced.

The invention discloses a multifrequency ultrasonic testing regression prediction method acid value of transformer oil. The method comprises the following steps of 1), performing multifrequency ultrasonic characteristic testing and acid value measuring on a transformer oil sample, establishing a transformer oil acid value regression prediction model by means of a support vector regression machine;2), performing optimized combination of a punishment function punishment factor C, a kernel function parameter sigma and an insensitive loss function lost factor epsilon of the transformer coil acidvalue regression prediction model by means of a genetic algorithm; 3), establishing a transformer oil acid value multifrequency ultrasonic wave testing regression prediction model of the support vector regression machine based on the genetic algorithm; and 4), acquiring a multifrequency ultrasonic wave acoustic frequency spectrum of the transformer oil sample, and predicating the acid value in thetransformer oil. The multifrequency ultrasonic testing regression prediction method realizes acquisition of a predicated value of the acid value in the transformer oil through prediction and calculation, high fitting degree between the predicated value of the transformer oil acid value regression model which is established by the support vector machine through genetic algorithm optimization, andlow data error.

The invention relates to a mobile-phone screen angular point detection method based on matching of a Hough transform template. The method comprises the steps that 1) morphological transformation of images is used to preprocess a mobile-phone screen area, and interference signals as noises and Moire patterns; 2) an image obtained in the step 1) is reduced to a certain scale, an edge detection algorithm is used to find boundaries in the image, Hough transform is used to vote boundaries, straight line segments existing in the image are obtained, four most proper line segments are selected form a straight line segment set, and straight lines in which the four line segments are positioned can form a quadrangular screen area; and 3) an angular point template is generated adaptively by utilizing four included angles of the obtained quadrangular area, the template is further positioned accurately in areas near four vertexes of the quadrangle, and a final screen area detection result is obtained.

The invention relates to a fusarium graminearum caused rootstock rot seedling-stage resistance identification method comprising the following steps of sprouting measured wheat varieties or series seeds after sterilizing, and then inoculating activated fusarium graminearum; spreading the wheat seeds inoculated with the fusarium graminearum in a sterilized wet tissue, wrapping up, and keeping wet and culturing for 1 to 3 days under the shielding conditions, and then naturally growing for 11 to 13 days under natural lighting to form seedlings; immersing edges of the wet tissue in distilled water after the package layer of the surface of the wet tissue is dried during the natural growing period; and finally identifying the rootstock rot of the seedlings, and using the result as fusarium graminearum caused disease indexes of the measured wheat varieties or series seeds.

The invention provides a testing method and loading device for reinforced concrete bond-slip performance based on corrosion and fatigue load coupling influence. The device comprises an external reaction frame and is characterized in that an MTS testing machine is arranged on the external reaction frame, and a conversion connector and an anchor are mounted at the end of the MTS testing machine; an internal reaction frame is arranged right below the MTS testing machine and provided with a station for placing a to-be-tested block, and the station is a square space jointly formed by a first retaining plate, a second retaining plate, a first fastening screw and a second fastening screw in an enclosed manner; a first clamp is mounted at the top end of the first retaining plate, and a first displacement sensor is fixed on the first clamp; a second clamp is mounted at the bottom end of the second retaining plate, and a second displacement sensor is fixed on the second clamp. The testing method and loading device has the advantages that parameters such as reinforced concrete bond-slip performance under corrosion and fatigue load coupling influence can be measured objectively and accurately, and the method is simple and convenient in testing.